JP7544864B2 - High density micro-fulfillment center with overnight batch pick replenishment of G2P storage from the store floor "HD-MFC" and method of operation - Google Patents

Description

CLAIM OF PRIORITY This application claims priority to U.S. Provisional Patent Application No. 63/067,759, filed August 19, 2020, entitled "High Density Micro Fulfillment Center "HD-MFC" With Nightly G2P Storage Batch Pick Replenishment from Store Floor and Method of Operating Same," which is incorporated herein by reference in its entirety.

This application claims priority to U.S. Provisional Patent Application No. 63/030,662, filed May 27, 2020, entitled "Micro-Fulfillment Center and Method of Operating a Micro-Fulfillment Center," which is incorporated herein by reference in its entirety.

This application claims priority to U.S. Provisional Patent Application No. 63/060,994, filed August 4, 2020, entitled "Micro-Fulfillment Center with Nightly Replenishment and Order Fill of Transient Inventory and Method of Operating Same," which is incorporated herein by reference in its entirety.

The most challenging problem facing supermarket operators today is finding a way to profitably meet the growing market demand for online grocery services. Their grocery prices are based on the self-service retail store model, where customers provide free labor to the retailer by selecting their own orders. However, the e-commerce model requires the retailer to select and forward the order to the customer. Moreover, they are constrained from raising prices to offset these additional costs by the intense competitive pressures in this highly price-driven trade category.

Fulfilling online orders from a retailer's existing self-service stores has many compelling advantages over building a separate facility for this purpose. However, it also poses several difficult problems, a major one being the labor costs associated with picking and processing the orders. Retailers typically use a route-picking version of picker-to-goods (P2G) picking, and additional labor costs are incurred in storing, retrieving, and distributing completed orders from the store to picking customers or delivery drivers. These labor costs are so high that it is currently virtually impossible for retailers to realize a profit from online services using this model.

A second major problem with in-store picking is that self-service stores are fairly chaotic environments, making it very difficult for retailers to maintain accurate information about the on-hand inventory of all the 40,000 or so products typically sold in each of their stores, and therefore stock-outs are not uncommon. Self-service stores can operate successfully with relatively inaccurate inventory data because customers who discover that a product is out of stock decide for themselves whether to purchase a replacement product or give up on the purchase at that time. However, with online ordering, this decision must be made by the retailer, and substitutions and stock-outs are known to be the largest causes of customer dissatisfaction with online groceries. A third major problem with in-store fulfillment is that large multiple order carts block aisles and worsen the experience of customers who are picking their own orders (and thus contributing to a higher profit margin for the retailer than online orders that are picked by pickers). Thus, there is a significant risk that customers will become so inconvenienced that they will switch to shopping at a different retailer's store.

To overcome these challenges of in-store fulfillment, retailers are currently experimenting with automation technologies that are deployed in-store or installed in-store that perform a goods-to-picker (G2P) order picking process in which the products to be picked are typically stored in totes or other containers in the system, and the product totes containing the ordered SKUs are transported through a picking workstation where a stationary human (or robotic) picker transfers the ordered individual items from the product totes to the order container. This technology solution addresses all three major problems associated with P2G picking mentioned above. Stationary G2P pickers can pick many more individual items per hour than mobile P2G pickers, which can dramatically reduce the labor costs of picking (and labor costs would be reduced even further if robotic pickers were used for this task). In addition, the automated system can store, retrieve, and distribute completed orders, thereby reducing or eliminating the labor costs associated with these additional processing tasks. Furthermore, when inventory is stored in an automated G2P system, there is much more information about on-hand inventory than if the inventory was on shelves in the store, so substitutions and out-of-stocks are greatly reduced, thereby improving customer satisfaction. Finally, picking in an automated G2P system removes pickers from the store floor, thereby eliminating a source of inconvenience for self-service customers.

However, retailers must solve two closely related problems associated with installing automated G2P systems in their stores. Physical space is the first problem, since G2P systems require their own stock of inventory, separate from the self-service store, that is used as pick stock in fulfilling online orders. In addition, offering online customers all of the products that are in the store has been shown to be a key factor in getting customers to adopt online grocery, so limiting the assortment available to online customers to include only items that can fit into these smaller systems is a competitively suboptimal solution.

FIG. 1 is a block diagram of a store in accordance with an embodiment of the present technology.

FIG. 13 is a flowchart diagram illustrating store-wide replenishment and depletion of inventory in accordance with an embodiment of the present technology. FIG. 13 is a flowchart diagram illustrating store-wide replenishment and depletion of inventory in accordance with an embodiment of the present technology. FIG. 13 is a flowchart diagram illustrating store-wide replenishment and depletion of inventory in accordance with an embodiment of the present technology.

FIG. 13 is a flow chart diagram illustrating a method utilizing manual order screening with auto-storage and distribution of screened orders.

FIG. 1 is a flow chart diagram illustrating an exemplary HD-MFC store control and inventory replenishment system in a self-service store.

FIG. 13 is a flow chart diagram illustrating inventory replenishment order sorting in accordance with various embodiments of the present technology. FIG. 13 is a flow chart diagram illustrating inventory replenishment order sorting in accordance with various embodiments of the present technology.

1 is a block diagram illustrating an exemplary store site format in accordance with an embodiment of the present technology.

Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications. Material incorporated into this application from other applications.

Embodiments of the present technology will now be described with reference to drawings relating generally to micro-fulfillment centers and, more specifically, to methods of replenishment operations in micro-fulfillment centers.

It is understood that the present embodiments may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the invention to those skilled in the art. Indeed, the embodiments are intended to cover alterations, variations, and equivalents of these embodiments, which are included within the scope and concept of the invention as defined by the appended claims. Moreover, in the following detailed description, specific details are set forth in order to provide an understanding of the present embodiments.

The terms "top" and "bottom", "upper" and "lower", "vertical" and "horizontal", as used herein, are used for illustration and explanation only and are not meant to limit the description of the embodiments insofar as the referenced items are interchangeable in location and orientation. Also, as used herein, the terms "substantially" and/or "about" mean that a particular dimension or parameter may vary within acceptable manufacturing tolerances for a given application. In one non-limiting embodiment, the acceptable manufacturing tolerance is ±2.5%.

The disclosed store formats, operating systems, and methods may be used in conjunction with robotic picking systems and robotics, for example, as disclosed in U.S. Patent Application Publication No. US 2017/0313514 A1, “Order Fulfillment System,” published on November 2, 2017, which is incorporated herein by reference in its entirety. Similarly, the disclosed store formats, operating systems, and methods may be used in conjunction with robotic picking systems and robotics deployed in conjunction with retail store formats, for example, as disclosed in U.S. Patent Application Publication No. US 2018/0134492 A1, “Automated-Service Retail System and Method,” published on May 17, 2018, which is incorporated herein by reference in its entirety. Additionally, the store formats, operating systems, and methods disclosed herein may be implemented in accordance with, for example, U.S. Patent Application Publication No. US2018/0150793A1, published on May 31, 2018, entitled "Automated Retail Supply Chain and Inventory Management System," U.S. Patent Application Publication No. US2018/0194556A1, published on July 12, 2018, entitled "Interchangeable Automated Mobile Robots with a Plurality of Operating Modes Configuring a Plurality of Different Robot Tasks," and U.S. Patent Application Publication No. US2018/0194556A1, published on July 12, 2018, entitled "Interchangeable Automated Mobile Robots with a Plurality of Operating Modes Configuring a Plurality of Different Robot Tasks." The present invention may be used in conjunction with various elements of a fully or partially automated supply chain system, as disclosed in U.S. Patent Application Publication No. US2018/0247257A1, published on August 30, 2018, entitled "Inventory Management System and Method," and U.S. Patent Application Publication No. US2018/0341908A1, published on November 29, 2018, entitled "Fully Automated Self Service Store," all of which are incorporated herein by reference in their entireties.

The disclosed store formats, operating systems, and methods may be utilized in the aforementioned examples and further in applications such as those summarized in FIG. 1, by way of non-limiting example. FIG. 1 is a block diagram illustrating an example inventory replenishment management system 110 in a self-service store 116 in which some example embodiments of the present disclosure may be implemented. The example inventory replenishment management system 110 may be implemented in the self-service store 116 and may include an inventory management computing device 120, a sales floor area 130, a receiving area 140, an inventory storage and queuing area 150, a goods-to-picker (G2P) system 160, a database, and a network (not shown). The self-service retail store 116 is configured to fulfill retail store orders in a "self-service" model. A customer selects an item from the sales floor area 130 and pays for the item, thereby fulfilling each customer order in a "self-service" model. The self-service retail store 116 is further configured to fulfill retail store orders in an "e-commerce" model. In this model, a customer selects items from a software application, which may be based on a computer, cell phone, or other device. The software application allows the customer to select items from the application for an order to be fulfilled by the self-service retailer 116, either alone from inventory selected from within the G2P system 160 or in combination with inventory selected from the sales floor area 130. Instead of items being picked by the customer (from the sales floor) and assembled into an order, the items that make up an order in the "e-commerce" model are typically picked by an employee (or agent or automation) from the sales floor area 130 or the G2P system 160, assembled into an order, and delivered to the customer. The customer then retrieves or receives delivery of the order after the order has been assembled.

The G2P system or area 160 includes a material control system (MCS) 162, container storage 164, container transport 166, product selection module 168, filling module 172, container introduction module 174, and distribution module 176. In one example, the G2P system 160 may be an order fulfillment system for automated fulfillment of orders received, for example, via an e-commerce model. An embodiment of the G2P system may include, for example, a multi-level rack structure that holds the picking inventory. The G2P system further includes a workstation where a human or robotic picker receives receptacles or containers of individual items for transporting the individual items to the order container. Mobile vehicles or mobile robots are further provided, which are autonomous vehicles that perform various transfer and transportation functions within the G2P system, including handling the movement of containers of items between storage locations in the rack structure and the workstations. The G2P system may further include a centralized control system comprising computers, software, and communication components that manages the operation of the entire system. The G2P system may include one or more input/output interfaces where containers or individual items are introduced into the system to replenish pick inventory and where completed orders are released from the system for ultimate delivery to customers. Containers used to transport goods within G2P may be referred to herein as totes. Such totes may include sub-totes, which are smaller totes, dividers, or compartments within a tote to separate goods of different SKUs within the tote. It is understood that the G2P system may include various other components in addition to or in place of the aforementioned components.

The inventory management computing device 120 may be a local server or computer terminal located at the retail store 116. The inventory management computing device 120 may be a centralized control system or may function in conjunction with a centralized control system. The inventory management computing device 120 may include a processor 121 and a memory 124.

The exemplary inventory replenishment management system 110 may maintain a database that stores product information for each of the products in the entire inventory of the self-service retail store 116. The product information may include product name, product code, location code (e.g., zone, aisle, shelf, bin, etc.), frozen or refrigerated status, number of products displayed on the sales floor, category, department, priority to be dispensed, number of products to be dispensed, time to be dispensed, scheduled pick-up time, inventory status, and product supplier. The product code for each of the products may be a Universal Product Code (UPC) code, Quick Response (QR) code, or other standard code associated with product information stored in a database including the site data application 126 stored in memory 124. Products may be delivered to the self-service retail store 116 and unloaded at a receiving area, where the products may be packaged and received in containers on a pallet. Each of the bins may include a packaged common container or, alternatively, may include a packaged mixed container. Data associated with the received product may be scanned and read, and various information regarding the product may be retrieved from the database after the product is scanned into the database when it is received by the self-service retailer 116. For example, the location code of the product may be the location where the product is displayed within the sales floor 130, such as a zone, aisle, shelf, bin, etc. Similarly, the location code of the product may be the location where the product is stored within the G2P system 160, etc. The inventory status of the product may be indicated as "out of stock," "low inventory," or "standard inventory." Frozen or refrigerated products may have a higher offload priority to be distributed to the sales floor 130 or the G2P system 160. The product information may further include product specifications, such as dimensions, weight, shape, color, etc. The database may store other product information, such as scheduled pick-up times, pending customer orders, historical sales data, current and seasonal rates, or other attributes associated with each product sold within or fulfilled from the self-service retail store 116.

The inventory replenishment application 128 may be a software module or application stored in the memory 124 and executed by the processor 121 of the inventory management computing device 120. The inventory replenishment application 128 may be configured to rank and prioritize products received at the receiving area and staged at the inventory storage and queuing area 150 to determine the priority, time, and number of each product to be distributed to the sales floor 130 or the G2P system 160 of the self-service retail store 116, as described in more detail below. Additionally, the inventory replenishment application 128 may be configured to rank and prioritize products already distributed to the sales floor 130 to determine the priority, time, and number of each product to also be distributed to replenish the G2P system 160 of the self-service retail store 116, as described in more detail below. The inventory replenishment application 128 may be configured to analyze past sales data of sold products to obtain the sales pattern of the products. Additionally, the inventory replenishment application 128 may determine which products are needed for replenishment along with the number and time of product replenishment. The sales pattern of a particular product may include sales volume, velocity or sales speed, other sales information, or a combination of two or more of such sales information. The sales pattern of a product may be associated with timing information, such as time of day, time of week, time of month, and time of year. For example, some products may have higher sales volume over weekends compared to weekdays. Holidays may affect the sales pattern of a particular product. The inventory replenishment application 128 may be configured to rank the products to determine a priority, time, and number of each product to be distributed to the sales floor 130 or G2P system of the self-service retail store 116 or other locations based on the sales pattern and product information of each of the products. The inventory replenishment module 128 may determine the order of the products to be moved based on the sales pattern and current inventory status of the products to be ordered. Alternatively, the inventory replenishment application 128 may be further configured as described or in other manners.

Referring now to FIG. 2A, a flow diagram 210 is shown illustrating an example inventory replenishment management system 110 within a self-service store 116 in which some example embodiments of the present disclosure may be implemented. The upper portion 216 represents the replenishment of the store's inventory, while the lower portion 218 represents the depletion of the store's inventory. In practice, inventory replenishment and depletion may occur sequentially over time, or, more commonly, in parallel. Alternatively, inventory replenishment and depletion may occur sequentially and in parallel over time.

Replenishment inventory for the store may be received (220) at the receiving area 140 and queued (222) at the inventory storage and queuing area 150. The inventory replenishment application 128 transfers (226) the inventory, primarily in the form of containers, to either the store floor 130 or the G2P system 160. The inventory transferred to the store floor 130 comprises the sum of (1) the inventory needed to fulfill self-service orders, (2) the inventory transferred to the floor and needed to replenish the G2P system, and (3) the inventory needed to make up the floor-picked portion of the e-commerce orders fulfilled by the store. The inventory transferred to the sales floor 130 and needed to replenish the G2P system (226) typically comprises the lower velocity (lower sales velocity, e.g., units per day or SKU) inventory needed for e-commerce orders. In contrast, the inventory needed to replenish the G2P system that is transferred 226 to the G2P system 160 typically consists of inventory at a higher velocity (higher sales velocity, e.g., units per day or SKUs) required for e-commerce orders. The replenishment inventory transferred 226 to the sales floor 130 and the replenishment inventory transferred 226 to the G2P system 160 may be mutually exclusive, i.e., different SKUs are transferred 226 to the sales floor 130 than the SKUs transferred 226 to the G2P system 160, and the velocity of the SKUs transferred 226 to the sales floor 130 is low and sufficient to meet the demand for both self-service and e-commerce orders. Similarly, the replenishment inventory transferred (226) to the sales floor 130 and the replenishment inventory transferred (226) to the G2P system 160 may be common, i.e., for example, the same SKU containers are transferred (226) to both the sales floor 130 and the G2P system 160, and the velocity of the SKUs transferred (226) to both the sales floor 130 and the G2P system 160 is high to ensure that higher numbers are stocked at both locations based on the demand for self-service orders and e-commerce orders separately.

Inventory transferred (226) to the store floor 130 is replenished by defining replenishment trips (228), collecting bins of inventory based on those trips (232), and replenishing the store floor by stocking the store floor shelves (234). Inventory transferred (226) to the G2P system 160 is replenished by defining replenishment containers or totes to store the inventory (238), collecting bins of inventory based on those containers or totes to be filled with inventory (232), and loading the inventory into the G2P system (246) by removing the containers of external packaging, loading the inventory contents into the totes by a filling process in the filling section 172, and introducing the totes into the container storage structure 164 of the G2P system 160 (174). To complete the replenishment of the G2P system, the inventory transferred (226) to the sales floor 130 and required to replenish the G2P system must be further transferred (248) back to the G2P system to complete the P2G replenishment (310), as described with respect to FIG. 3.

Fulfillment of orders occurs in two models: a self-service model and an e-commerce model. In the "self-service" model, a customer selects or picks (252) the items that make up an order from the sales floor area 130 and pays for the items, thereby fulfilling (254) each of the customer's orders in the "self-service" model. In the "e-commerce" model, a customer selects the items from a software application, which may be based on a computer, a cell phone, or other device. The software application allows the customer to select items from the application for an order to be fulfilled by the self-service retailer 116, either alone from inventory picked (260) from within the G2P system 160 or in combination with inventory picked (262) from the sales floor area 130. Instead of items being picked by the customer (from the sales floor) and assembled into an order, the items that make up an order in the "e-commerce" model are typically picked by an employee (or agent or automation) from the sales floor area 130 or the G2P system 160 and assembled into an order (264) for delivery to the customer. The customer then takes delivery of or receives the order after it has been packaged and fulfills the e-commerce order (268).

Nearly all packaged goods SKUs in a supermarket are replenished by bins (i.e., the original containers in which the individual items were packaged at the supplier's plant for shipment to the retailer's distribution center). To minimize the number of replenishment transactions per day per store, and therefore the labor costs of replenishment, the number of individual items in each bin represents the number of weeks of supply for the majority of SKUs. This relatively excess inventory saves on replenishment labor costs, but requires sufficient shelf space to store all the bins plus a safety buffer. The lowest cost method of replenishing the G2P sorting system would leverage this existing infrastructure and still replenish by bin, but this method essentially requires the amount of individual items in totes in the G2P storage structure to be equivalent to that found on the shelves of the central store.

To maximize the number of SKUs that can be stored within a given number of totes, the interior volume of an individual tote can be further divided into separate compartments by using dividing panels (dividers) or interior containers (sub-totes) to create multi-SKU totes where each SKU is stored in a separate compartment. The smaller the average compartment size, the greater the "SKU density" (total number of SKUs divided by total number of product totes in storage), measured as the average number of SKUs per product tote.

Replenishing a standard store's entire assortment of packaged goods with bins results in a density of approximately 2 SKUs per tote, i.e., the individual items in an average-sized bin fit into a compartment that is one-half the total volume of the tote. High-velocity SKU bins typically contain more product than low-velocity SKUs, so their SKU density will be lower than the average, while low-velocity SKUs will have a higher density than the average. As an example, this average density means that in one example, 37,000 SKUs would require roughly 18,500 product totes, and few stores would be able to accommodate such a large system.

The first step in solving the problem is to select the SKUs to be manually picked (P2G) in the store to fulfill customer orders. Based on the description of SKU velocity strategies presented above, one strategy for doing this is an "all or nothing" approach, whereby the store is divided into zones and all customer order lines for SKUs in each zone are either all picked by P2G or all picked by G2P, in order to maintain pick density all along the route from pick to cart and ensure that the savings assumed from picking by automation are fully realized. Clearly, there are two parts of a traditional supermarket that would be ideal candidates for all manual picking: the "wet market", which may be along the periphery of the store, and the freezer aisle, which may be in the center store.

Wet markets include products such as produce, meat, seafood, and flowers. In a store containing a 40,000 SKU assortment, these fresh items may represent only 3,000 SKUs, but typically account for 20%-25% of the individual items ordered online. Manually picking these products from the store floor actually has three characteristics over picking in a G2P system. One characteristic comes from the fact that, unlike packaged goods, individual items of the same product vary significantly from one another. For example, one steak is not identical in marbling to another, and produce items may vary in ripeness and blemishes. To maintain customer satisfaction with fresh products, pickers can exercise judgment in selecting high quality individual items, and it is more cost-effective for this time-consuming selection process to be performed on the store floor than at a G2P sorting station, where additional operator time would limit machine throughput. Additionally, many of these products are "weight-insensitive" items, requiring a selected number to be weighed in order to be priced. Again, performing this process at the G2P workstation would reduce system throughput and therefore be more expensive than weighing on the floor. Finally, the high perishability of these products and the potential for contamination of other products makes them candidates for keeping them away from the G2P system and on the store floor where they can be easily accessed and viewed by store employees. Here, the location of the wet market along the periphery of the store means that the travel costs allocated per order line/each pick would be lower in the wet market than in other zones, since the pick density is much higher, given the much shorter travel distances for the order pickers, and the higher speeds of these SKUs, than within the labyrinthine central store aisles filled with packaged goods.

The second most logical zone for implementing all-manual P2G picking is the freezer aisle in the core store. In a typical U.S. supermarket, frozen SKUs account for approximately 10% of all packaged goods SKUs and 12%-15% of packaged individual items sold. Similar to the wet market, the freezer aisle has a relatively high P2G pick density spread over a limited travel distance, making the cost per order line/individual item lower in this zone than any other area of the core store. Additionally, frozen SKUs tend to be larger than non-frozen SKUs, which reduces SKU density in the G2P system, and the additional space required for refrigeration equipment and air circulation can further reduce the total volume space available for product storage in the system.

All of the non-frozen packaged goods (NFPG), including roughly 33,000 of the total 40,000 SKUs in the exemplary store, are distributed throughout other parts of the central store. While the potential labor savings realized within each aisle can be determined and that metric used to determine which sets of aisles to dedicate to G2P picking or P2G picking, it is still difficult to fit enough product into a small system to achieve sufficient labor savings to justify the investment. However, there is another approach to integrating a small automated G2P individual product picking system into a self-service store that allows picking of all order lines for NFPG SKUs in the G2P system. This approach can be called the "SKU density" strategy. Although features of the disclosed embodiments may be applied to selecting a subset of the individual products required to fulfill a particular e-commerce order in a G2P system, the disclosed embodiments may alternatively be applied to selecting an entire order or a complete order from a G2P system, or to selecting any combination of individual products from a G2P system.

The system and method abandons refilling the G2P system with containers except for a small subset of the highest velocity SKUs, and most of the remaining SKUs are refilled with individual items. As an example, instead of selecting a subset of NFPG SKUs to store in the system, the disclosed method largely abandons refilling containers in the G2P system in favor of refilling with individual items, i.e., the refill count of most of the SKUs in the G2P system is less than the number of containers. Only a small subset of high velocity SKUs (e.g., only SKUs that sell more than one-half container per day to online customers) are transferred (226) to the G2P system 160 to be refilled with containers, and all of the remaining SKUs are refilled with individual items (by G2P refill 310 from the store floor 130). The reduction in refill count allows SKUs to be stored in smaller compartments within a multi-SKU tote, greatly increasing SKU density and allowing the same number of totes to hold many more SKUs. Returning to the exemplary store containing 33,000 NFPG SKUs, only 1,000 SKUs at the highest velocity may be replenished by bins and loaded into full totes plus half tote sections and third tote sections to achieve an average density of approximately 1 SKU per tote, thus requiring approximately 1,000 totes in the G2P system. The other 32,000 SKUs are replenished by individual items using quarter tote sections and sixth tote sections to obtain an average density of 5 SKU per tote. These 32,000 SKUs then require only an additional 6,400 totes in the G2P system. Thus, the combined total of 7,400 product totes required to hold the entire NFPG assortment of 33,000 SKUs under this "SKU density" strategy is only about 2,400 more tote positions than would be required for the 5,000 highest velocity SKUs under a SKU velocity strategy with a SKU density of 1 SKU per tote. This number of totes is still a small enough amount of additional storage capacity to fit in most stores.

This approach can be counterintuitive because individual item replenishment is inherently more labor intensive than container replenishment, making it impractical and expensive to replenish a G2P system with individual items from a distribution center designed to ship containers. Fortunately, there is another readily accessible and very practical source of individual items that can be picked to replenish the system: the store shelves. The key innovation in this method of integrating G2P automation into the store is to manually pick individual items from the store shelves to replenish the G2P instead of fulfilling customer orders with much higher labor efficiency. Over time, the same number of individual items are picked for these replenishment orders as were picked for customer orders for the same SKUs, but the method and timing of picking and the resulting efficiencies are significantly different.

2B and 2C, a flow diagram is shown illustrating an example inventory replenishment management system in a self-service store in which some example embodiments of the present disclosure may be implemented. In a high-density Micro Fulfillment Center (MFC) model, overnight batch picking to replenish the MFC inventory enables the concept of a "virtual inventory." In addition to allocating storage capacity to hold "fixed" or "static" inventory used to fulfill future (anticipated) orders, a portion of the storage capacity is also allocated to hold "temporary" or "dynamic" inventory to fulfill certain known orders (e.g., non-same-day orders) after a short time frame. In the G2P system, static storage corresponds to persistent stock (higher rate stock replenished by containers in normal fill cycles and/or lower rate stock replenished at sub-container level from the store floor in normal batch pick replenishment cycles), while temporary storage corresponds to dynamic stock (stock determined by non-same-day orders entered into the G2P system, e.g., to fulfill specific orders only at night or during off-peak hours). In accordance with the present technology, the store fulfills same-day orders by combining (a) picking from the G2P static storage and (b) picking directly from the floor, while the store fulfills non-same-day orders by receiving (b) picked from the floor (as if it were a same-day order), e.g., overnight, introducing (b) into temporary storage in the G2P system, and the next day (or whenever it needs to be fulfilled) picking the entire order (a)+(b) from the G2P system.

The specific configuration of storage capacity allocated in the G2P system in terms of the number of totes and the number and size of secondary totes is determined by an algorithm and can change from day to day. The product assortment offered by the retailer to the customer for pick or delivery on the day includes only SKUs in the static inventory in the MFC, plus SKUs that are picked and combined in response to orders from the store floor. However, the product assortment offered to the customer for pick or delivery on subsequent days may include all of the transportable products in the store and in the static inventory storage of the G2P system, and this combination can be picked entirely from the G2P system as described. Every night, store employees run a batch picking process to replenish the majority of the SKUs in the static inventory using individual items picked from the store floor (a number of the highest velocity SKUs are replenished by bins and not by this batch picking process). Each SKU included in the assortment has a persistent inventory, but the size of the secondary totes and the number of replenishments can change with each replenishment transaction. In general, the system attempts to replenish the maximum number of individual items that will fit into a secondary tote of a specified size for each SKU to minimize replenishment transactions. SKUs that are in an assortment with dynamic stock and therefore do not have persistent stock are replenished only when needed to fulfill known orders placed for later (e.g., next day) picking or delivery so that they can be batch picked in the same pass through the store that collects the individual items to replenish the static stock. A hybrid approach is also possible, whereby static stock is held for a particular SKU, but only for the number of individual items expected to be ordered for pick/delivery that day, and all overnight orders are replenished to the dynamic stock for immediate fulfillment. In this context, "batch picking" is contrasted with "order picking." As will be described in more detail below with respect to Figures 2B and 2C, batch picking may be utilized where all individual items may be picked to fulfill a particular set of orders, where the individual items may be picked within a product sequence and aggregated/placed into a common container or tote containing sub-totes (e.g., a single sku/sub-tote, but containing multiple individual items per sub-tote to fulfill a set of orders), and these batch picked totes are then introduced into the G2P system as inventory and subject to "secondary sorting" within the G2P system, after which an "order pick" sequence occurs to pick a specific order, where the specific order is picked from inventory within the G2P system and placed into an order tote. Additionally, in this context, static or persistent storage and inventory may refer to inventory that is stored, awaiting future unknown orders, and that is replenished when low, for example, by bins in the G2P system for fast skus (see 160 in FIG. 2B) or by secondary bins from the floor to the G2P system as described in FIG. 2A for slow skus (see also 520 in FIG. 2B). The common element of static or persistent storage and inventory is that it is provided and awaiting future unknown orders. In contrast, in this context, temporary or dynamic storage and inventory may refer to inventory that is stored in response to existing orders or future known orders, and that is replenished in the G2P system in its nature as inventory that is batch picked in response to an order, for example, for next day or non-same day orders (see 520 in FIG. 2B) and introduced into the G2P system for subsequent order picking (see 522 in FIG. 2B) operations performed to fulfill a particular order. Here, batch picking may be utilized to replenish static or persistent inventory at a predefined inventory level (see 310 in FIG. 2B), or alternatively, to replenish temporary or dynamic inventory at an inventory level to fulfill a particular set of orders (see 520 in FIG. 2B). As a non-limiting example, in a batch pick replenishment of temporary or dynamic inventory with subsequent order pick secondary sorting examples, as described in more detail below, if n next day orders require m sku xyz, then n×m sku xyz are batch picked overnight (520) to replenish the dynamic inventory of the G2P system for the next day's order pick operation, and during the next day, n order pick operations occur to reduce the n×m sku from the product tote that stores the xyz sku and transfer the xyz sku to the order tote to fulfill the n orders. As described, the G2P system provides e-commerce delivery as a result of next day ordering and may include a "virtual inventory" reflecting the entire store's inventory (floor + G2P static/persistent) that can be stored in the G2P system without maintaining in the G2P system all of the sku on the floor that is not included in the G2P static/persistent inventory. As a result, a much higher rate of sku can be provided through the G2P system without maintaining in the G2P system the diverse G2P static/persistent inventory that is maintained on the floor of a self-service store.

2B, a flow diagram 210' is shown illustrating an example inventory replenishment management system in a self-service store in which some example embodiments of the present disclosure may be implemented. Flow diagram 210' has similar features to flow diagram 210, but adds the concept of allocating storage capacity in the G2P system for temporary replenishment and selecting G2P order-based replenishment from the store floor for non-same-day orders, as described in detail below. As with flow diagram 210, the upper portion 216 represents the replenishment of the store's inventory, while the lower portion 218 represents the depletion of the store's inventory. In practice, inventory replenishment and depletion may occur sequentially over time, or more commonly, in parallel. Alternatively, inventory replenishment and depletion may occur sequentially and in parallel over time.

Replenishment inventory for the store may be received (220) at the receiving area 140 and queued (222) at the inventory storage and queuing area 150. The inventory replenishment application 128 transfers (226) the inventory, primarily in the form of containers, to either the store floor 130 or the G2P system 160. The inventory transferred to the store floor 130 constitutes the sum of (1) the inventory needed to fulfill self-service orders, (2) the lower velocity persistent inventory transferred to the floor that is needed to replenish the G2P system, and (3) the inventory needed to make up the floor-based portion of the e-commerce orders fulfilled by the store. As described, the inventory needed to make up the floor-based portion of the e-commerce orders fulfilled by the store may be picked directly from the floor to fulfill same-day orders, or alternatively, transferred to the G2P system for order-based G2P dynamic inventory to fulfill non-same-day orders by the G2P system. The inventory transferred 226 to the sales floor 130 and required to replenish the G2P system's standing inventory is typically comprised of inventory with a lower velocity (lower sales velocity, e.g., units or SKUs per day) required for e-commerce orders, whereas the inventory transferred 226 to the G2P system 160 and required to replenish the G2P system is typically comprised of inventory with a higher velocity (higher sales velocity, e.g., units or SKUs per day) required for e-commerce orders. The replenishment inventory transferred 226 to the sales floor 130 and the replenishment inventory transferred 226 to the G2P system 160 may be mutually exclusive, i.e., for example, SKUs transferred 226 to the sales floor 130 that are different from the SKUs transferred 226 to the G2P system 160, and the velocity of the SKUs transferred 226 to the sales floor 130 is low and sufficient to meet the demand for both self-service and e-commerce orders. Similarly, the replenishment inventory transferred (226) to the sales floor 130 and the replenishment inventory transferred (226) to the G2P system 160 may be common, i.e., for example, the same SKU containers are transferred (226) to both the sales floor 130 and the G2P system 160, and the velocity of the SKUs transferred (226) to both the sales floor 130 and the G2P system 160 is high to ensure that higher numbers are stocked at both locations based on the demand for self-service orders and e-commerce orders separately.

The inventory transferred (226) to the store floor 130 is replenished by defining replenishment trips (228), collecting containers of inventory based on those trips (232), and stocking the store floor shelves to replenish the store floor (234). The inventory initially transferred (226) to the G2P system 160 is destined for static storage in the G2P system, where storage capacity in the G2P system is allocated (506) based on static temporary capacity and assigned to defined static containers (508) and defined temporary containers (510), which reflect the respective allocation of containers. The higher velocity sustained inventory is assigned to the static replenishment containers. The higher velocity persistent inventory transferred (226) to the G2P system 160 is replenished by defining (508) static replenishment containers or totes to store the inventory, collecting (242) containers of inventory based on those containers or totes to be filled with inventory (508), and loading (246) the inventory into the G2P system by removing the containers of external packaging, loading the inventory contents into the totes by a filling process in the filling department 172, and introducing (174) the totes into the container storage structure 164 of the G2P system 160. To complete the static replenishment of the G2P system, the lower velocity persistent inventory transferred (226) to the sales floor 130 and required to replenish the G2P system needs to be further transferred (248) backwards to the G2P system to complete the replenishment of the G2P (310), as described with respect to FIG. 3.

Order fulfillment occurs through three models: self-service model, same-day e-commerce model, and non-same-day e-commerce model.

In a "self-service" model, a customer selects or picks (252) the items that make up an order from the sales floor area 130 and pays for the items, thereby fulfilling (254) each of the customer's orders in the "self-service" model.

In a same-day "e-commerce" model, a customer selects items from a software application, which may be based on a computer, cell phone, or other device. The software application allows the customer to select items from the application for an order to be fulfilled by the self-service retailer 116, either alone from inventory picked (260) from within the G2P system 160, or in combination with inventory picked (262) from the sales floor area 130. Instead of items being picked by the customer (from the sales floor) and assembled into an order, the items that make up an order in a same-day "e-commerce" model are typically picked by an employee (or agent or automation) from the sales floor area 130 or the G2P system 160 and assembled (264) into an order and delivered to the customer. After the order is assembled, the customer then obtains or receives delivery of the order and fulfills the e-commerce order (268).

In a non-same-day "e-commerce" model, a customer selects items from a software application that may be based on a computer, cell phone, or other device. The software application allows the customer to select items from the application for an order to be fulfilled by the self-service retail store 116, either alone from inventory picked (260) from within the G2P system 160 or in combination with inventory picked (262) from the sales floor area 130. Instead of items being picked by the customer (from the sales floor) and packaged into an order, the items that make up an order in a non-same-day "e-commerce" model may ultimately be picked from the G2P system, which utilizes a combination of static inventory (higher velocity persistent G2P inventory + lower velocity persistent G2P inventory transferred from the store floor) in combination with temporary inventory picked specifically from the store floor to fulfill the non-same-day "e-commerce" order; for example, inventory picked from the store floor for temporary G2P replenishment may be picked overnight or during off-peak hours. Here, store floor inventory 130 may be transferred (514) for next day orders (518) to replenish temporary inventory based on G2P orders picked from the store floor (520). Note that floor based inventory needed to fulfill self-service or same day e-commerce orders (516) remains on the floor for picking (252, 262) as described. Non-same day "e-commerce" orders may then be picked completely from the G2P system (522), taking inventory from a combination of persistent static inventory and temporary dynamic inventory currently in the G2P system to fulfill non-same day e-commerce orders after the orders are consolidated from the G2P system (524).

2C, a flow diagram 610 is shown further illustrating the two models described for fulfilling e-commerce orders: same-day e-commerce model and non-same-day e-commerce model. An order or stream of orders may be received by a fulfillment location or fulfillment center (612). Typically, inventory is checked to determine availability of items (614). If inventory is not available (618), the unavailable items are checked against the order to determine if substitutions are allowed (620). If substitutions are not allowed (622), a restocking transaction may be triggered (624) and the order may proceed without the missing items or may maintain the missing items on hold. If substitutions are allowed (626), substitutions are similarly checked for inventory, and with all items in stock or otherwise available (630), the order may proceed to fulfillment. The particular order is screened (632) for same-day pickup. If the order is for same-day pickup (634), the floor portion of the e-commerce order is picked (636), the static G2P portion of the e-commerce order is picked, the two are combined (640), and the e-commerce order is fulfilled (642). If the order is for non-same-day pickup (650), the floor portion of the e-commerce order is picked (652) and the temporary G2P storage is replenished using the floor portion of the e-commerce order (654). At this point, the entire e-commerce order (floor-based portion + G2P-based portion) is held in static temporary storage in the G2P system. Prior to fulfillment, the entire e-commerce order is picked (656) from the static temporary storage in the G2P system and fulfilled (658). In an alternative embodiment, in addition to the items picked from the G2P system, a particular e-commerce order may be supplemented and combined with items picked from the floor or otherwise picked (e.g., items that do not fit in the G2P system or items added to the order later and do not have enough time). In an alternative embodiment, if a particular customer does not get a particular order or cancels it, and the inventory in the temporary storage becomes excessive, a "reverse pick" may be envisioned, and the associated inventory in the temporary inventory of the G2P system may be transferred backwards from the G2P system to the floor. In the context of this description, "same day" may be equivalent to a period of time that does not allow for order-based replenishment 520 and subsequent picking 522. Thus, whether occurring on the same day or the next day, "same day" may be equivalent to, for example, a few hours or another time less, and "next day" or "non-same day" may be equivalent to, for example, a few hours or another time more.

Now referring to FIG. 2D, a flow diagram 700 is shown illustrating the flow of an exemplary order fulfillment system. This method is described as a system where orders are sorted and introduced to automation, which may be utilized alone or in combination with the methods previously described. Here, order sorting is already performed on the floor, and therefore for these orders, no separate sorting operation is required prior to fulfilling these orders (whereas in HD-MFC, a separate order sorting operation is performed by the G2P system or AS/RS with separate sorting capabilities after floor-based batch sorting or replenishment operations). Here, a storage capacity that may or may not be automated and does not incorporate a sorting operation may be utilized to fulfill the orders. Alternatively, a G2P system may be utilized as described, but within the G2P system in this method, sorting automation (e.g., a sorting workstation) is not utilized for this subset of orders. In an alternative aspect, the methods illustrated in FIG. 2A-D may be combined to leverage a particular G2P system with various fulfillment models.

As an example, loading orders into the ASRS/G2P system, which then interfaces directly with customers, as described with respect to FIG. 2D, is distinct from, but potentially complementary to, the model employed to load inventory into the G2P system and have the G2P system create orders that are distributed to customers; these are two different but potentially complementary models, first disclosed with respect to FIG. 2D. A second use of a particular G2P system is central to the HD-MFC model. The picking sequence of FIGS. 2B and 2C shows a batch picking (520) of individual items followed by secondary sorting (522), where a goods-to-person individual item picking system is used to perform this secondary sorting process. In contrast, the method disclosed in FIG. 2D utilizes floor-based order picking followed by storage in the ASRS to await further fulfillment.

Method 700 shown in FIG. 2D illustrates a model in which up to 100% of the items come from store floor inventory, as described below. The AS/RS can be an Alphabot (3D Shuttle), 2D Shuttle, 1D Shuttle, or Paternoster Stocker, or other suitable ASRS system, where orders are fulfilled by picking from store inventory at the store level and loading into the AS/AR for direct distribution to customers. The AS/RS for direct distribution to customers can be as disclosed in U.S. Patent Application Publication No. US 2017/0313514 A1, “Order Fulfillment System,” published November 2, 2017, which is incorporated herein by reference in its entirety. Alternatively, any AS/RS system can be utilized to store containers that can hold the individual items that make up a pre-picked order, for example. In the method of Figure 2D, sundries forming an order are picked and loaded into an ASRS for distribution of completed orders. Picking schedules for overnight or off-peak hours may be utilized to pick the orders, and rack-based batch picking carts may be utilized to perform order picking, either alone or in combination with batch picking, perhaps as a container, for example, for automated loading and unloading of totes or containers to and from the AS/RS. Unloading may be distribution from the same AS/RS filled from the interior stores directly to the parking lot. The racks and hardware for direct-to-customer distribution may be as disclosed in U.S. Patent Application Publication No. US2018/0194556A1, entitled "Interchangeable Automated Mobile Robots with a Plurality of Operating Modes Configuring a Plurality of Different Robot Task Capabilities," published July 12, 2018, which is incorporated herein by reference in its entirety.

In the method 700 shown in FIG. 2D, a customer order is received (712), e.g., before 10 p.m., a predefined time, or another time, on the day before the customer order is to be retrieved. Inventory is confirmed (718), order lines are completed, orders are known, and an optimized route for a picker may be defined, e.g., as described with respect to FIG. 2C. A picking sequence 720 may be as described with respect to FIG. 3 below, except that order lines are defined to fulfill the order, as opposed to refilling inventory, and containers are also provided to store the picked order, as opposed to refilling inventory. Picking of the order may be over a particular selected picking time interval (722), which may vary by season, time of week, or other time, e.g., the picking time interval is between 10 p.m. and 4 a.m., during which a picker manually picks items from inventory on store shelves (724). Here, this picking period may be adjusted to accommodate store replenishment before or after this batch picking period. Overnight batch picking has features including the batch picker being able to pick very efficiently since all orders are known and an optimized route for the picker can be defined. Furthermore, since the picker has many more orders to pick, a very efficient picking route can be defined. Furthermore, since it is picking at off-peak hours, customers of the store are not impeding the picking operation (where retail customers may or may not be present). This feature also improves the customer shopping experience by picking at night or off-peak hours so that the picker and picking cart are not impeding customer traffic. Additional features are provided in which overnight picking of batch or order picking or picking at off-peak hours allows a particular picker to achieve higher picking speeds and therefore more cost-effective, for example overnight picking of batch or order picking may be expected to deliver 250 or more individual items per hour as opposed to picking orders of 80-100 individual items per hour during the day. Upon completion of a particular batch pick, the batch picker loads (730) the picked orders into the AS/RS, which may be a mobile robot-based system or other suitable ASRS. In one aspect, the carts or racks used for batch picking may be attached to an Alphabot structure to allow direct unloading of totes full of customer orders and reloading of empty totes for the next batch pick run. Such a system is described in U.S. Provisional Patent Application No. 63/013,504, entitled "Transport Rack Cartridge," filed April 21, 2020, which is incorporated herein by reference in its entirety. The AS/RS storage may include room temperature zones, refrigerated temperature zones, and freezer temperature zones. Alternatively, the AS/RS storage may include an all-room temperature zone and store passively cooled totes (refrigerated and frozen), as disclosed, for example, in U.S. Patent Application No. 16/831,468, filed March 26, 2020, entitled "Tote Handling for Chilled or Frozen Goods," which is incorporated herein by reference in its entirety. When the order is ready to be fulfilled, it may be dispensed (734) from the ASRS and then fulfilled (738). In the disclosed embodiment, by way of example, the AS/RS may have the ability to present a fully integrated order directly to the customer, thereby substantially eliminating the labor costs associated with manually distributing orders to customers. In alternative aspects, the order may be fulfilled to the customer by any suitable method.

2E, a flow diagram 740 is shown illustrating an exemplary storage management and inventory replenishment management system in a self-service store 116 in which some example embodiments of the present disclosure (particularly the "HD-MFC" method described below) may be implemented. As a prelude, the "Reference MFC System Method of Operation" may be characterized by the method shown in FIG. 2A, but with block 310 removed (i.e., without the G2P replenishment portion 310). Here, a bot in the G2P system picks 260 an amount of "transportable" packaged goods assortment that will fit into the G2P system. Perishable goods and remaining packaged goods are manually picked (262) from the floor. Using in-store bin replenishment (the floor may be replenished from the DC by bin or break pack, and the G2P may be replenished from the DC by bin or break pack (246)), the G2P system may support, as a non-limiting example, 15,000-20,000 SKUs. Alternatively, using secondary tote replenishment from the DC, the G2P system can accommodate twice that number and encompass a nearly complete assortment of grocery packaged goods. In contrast to the "Reference MFC System Method of Operation" discussed above, this method of operation, as disclosed, has evolved into what may be called a "high velocity" method, whereby the G2P automated system is used to pick the highest velocity SKUs covering, for example, 80% of the individual items ordered, and slower moving SKUs are subsequently picked to be ordered manually from the floor. This described approach may be referred to as a high velocity micro-fulfillment strategy or "HV-MFC" method. As described in more detail below, an alternative method is developed that may be referred to as a "high density" operating method (High Density Micro Fulfillment Center or "HD-MFC"). This method may be applied, by way of example, when a large "GM" (General Merchandise) assortment is offered in-store, furthering the goal of integrating that assortment with grocery items as part of the pick-up and delivery.

The HD-MFC method may utilize a G2P system (or a suitable ASRS system using individual item picking) that provides an exemplary goods-to-picker automation system, such a system (in the example of the Alphabot G2P system) can operate with no single points of failure and includes fully robotic, fully random access to all storage and workstations within a three-dimensional workspace. The Alphabot G2P system is designed to be compact and space-efficient with efficient use of vertical space and includes a product storage architecture that maximizes SKU density. The design of this method of operation addresses how to best use this capacity to reduce the operational costs of fulfilling online orders within the store. The HD-MFC may be used with an integrated "in-store" G2P system as shown in FIG. 1, or an on-site or local G2P system as shown in FIG. 4, or with a store format that otherwise includes a G2P system. As described in detail below, the HD-MFC may be compared to the HV-MFC by the following characteristics:
1. HD-MFCs require smaller space requirements and lower capital costs (important features for in-store MFCs).
2. HD-MFC's labor costs are the same or lower.
3. HD-MFC simplifies the replenishment of MFC, while HV-MFC has higher replenishment complexity.
4. HD-MFCs more effectively eliminate in-store order sorting, which frustrates self-service customers.
5. HD-MFC enables faster order completion times, improving the customer experience.
6. HD-MFC allows for higher density picking of orders, fewer order totes per order, and lower distribution and delivery costs.
7. HD-MFC can be more effective in reducing substitutions and out-of-stocks.
8. HD-MFCs cost-effectively integrate general merchandise assortment with grocery P&D, delivering higher service levels at more affordable costs.

2E, a flow diagram 740 is shown illustrating an example storage management and inventory replenishment management system in a self-service store 116 in which some example embodiments of the present disclosure may be implemented. For simplicity, the method of the HD-MFC embodiment described with respect to FIG. 2E is shown, but features disclosed with respect to other embodiments may be combined. The upper portion 216 represents the replenishment of the store's inventory, while the lower portion 218 represents the depletion of the store's inventory. In practice, the replenishment and depletion of inventory may occur sequentially over time, or more generally, in parallel. Alternatively, the replenishment and depletion of inventory may occur sequentially and in parallel over time. In the HD-MFC model, the overall site replenishment is defined (748) as the customer demand for the store or facility. Now, if the store is appropriately replenished based on the store's demand, the G2P system in a store format where there are various classifications of storage, for example, based on the store's shelves or based on G2P totes and sub-totes, is appropriately replenished. Replenishment inventory for the store may be received (750) at the receiving area 140 and queued (752) at the inventory storage and queuing area 150. The inventory replenishment application 128 sends inventory, primarily in the form of containers, to the store floor. Inventory sent to the store floor may be transferred to shelves or other storage, with store floor storage (shelves) being the same as buffer storage for both the G2P system and the self-service floor. Although "buffer storage" is described as store floor shelves, shelves and/or buffer storage may include any suitable storage that may or may not be included on the store floor accessible by self-service customers. Inventory sent to the store floor is replenished by defining replenishment trips (754), collecting containers of inventory based on those trips (756), and stocking store floor shelves to replenish the store floor (758). To replenish the G2P system, inventory needed to replenish the G2P system is removed (760) from the sales floor and transferred to the G2P system to complete P2G replenishment (764), as described below with respect to Figures 3A and 3B.

3A, a P2G replenishment order picking process 310 is shown that includes the following steps. At intervals, such as daily, in G2P automation, software generates a list of replenishment order lines (320), with each order line specifying the identity of the SKU to be replenished, the shelf location in the store where the SKU is located, the desired number of individual items to be picked from the shelf, and the size of the bay in which the individual items will be placed (e.g., either 1/4 of a tote box or 1/6 of a tote box, but could be other sizes, such as 1/3 of a tote box). This pick list is then sorted (324) based on the shelf location of the SKU and further divided into trips (326), with each trip requiring a picker to push a cart on a specified path and pick the order lines on the pick list at a series of locations. The number of trips and the path of each trip depend on the number of order lines, the mix of defined bay sizes in which the individual items will be placed (330), and the number of totes (containers) that can be loaded onto the cart per trip (328). Carts are then set up and configured for each trip (332). With few exceptions, every cart on every trip is loaded with the maximum number of totes that the cart can carry, but with a mix of totes including 1/4 tote compartments and 1/6 tote compartments depending on the requirements for each trip. These totes usually come out of the G2P system after a de-fragmentation process that consolidates empty compartments into these refill totes. Each tote and each compartment within a tote contains some form of indicia (e.g., barcode) that contains a unique identifier, and all of the indicia are registered in the system along with the association/configuration between the tote and the compartment. Ideally, each cart is configured to include a storage array that holds all of the tote boxes that are filled on the trip, and a receiving shelf that holds two tote boxes at an ergonomically optimal height, one tote box configured using 1/4 tote compartments and the other configured using 1/6 tote compartments. The picker then performs each trip (334) by pushing the cart along a specified path, stopping successively at all SKU locations on the location-sorted pick list and transferring up to a specified number of individual items from all SKUs to a specified size bay in one of two totes on the receiving shelf (provided that the requested individual items are actually available on the shelf for picking). Note that any bay of the correct size in the receiving bin can be used and that after the receiving bin is filled, it is returned to the cart storage area and a replacement containing the same size bay is placed on the receiving shelf to be filled next. A computing device attached to the cart (or worn by the picker) provides the picker with the necessary information for each pick (SKU identification, shelf location, number of individual items, and size of the bay where the picked individual items will go), and the picker uses a barcode scanner to scan both the GTIN barcodes present on the picked individual items and on the bay where the individual items will go (a very advantageous scanner configuration is a finger-mounted "ring" scanner that allows the picker full use of both hands at all times). After the trip is completed, the picker pushes the cart full of filled totes to delivery station 174 connected to G2P picking system 160 (336), which transfers the totes from the cart to the G2P system to be placed in tote storage 164 as product totes ready to supply individual items to be picked at the G2P picking station to fulfill future customer orders. The procedure by which these totes are introduced into the G2P system is system specific. All of this restocking can be performed during normal business hours, or alternatively, during off-peak hours to allow for better floor flow and less overall crowding for store customers.

On the surface, this process model appears to violate a common rule of material handling system design that minimizes the number of times an item is touched. In both P2G and G2P picking using bin replenishment, each item is touched only twice, once at replenishment when the item is placed on the shelf or loaded into a tote, and once when the item is picked for a customer order. The disclosed model suggests that every individual item picked for a replenishment order as described above is touched three times, once when it is placed on the shelf, once when it is picked from the shelf for a replenishment order, and finally when it is picked for a customer order at the G2P picking station. However, less-than-bin store replenishment typically requires that an individual item be touched twice, once at the distribution center when the individual item is removed from the shipping bin for shipment to the store, and once when the item is placed on the shelf in the store. In contrast, in the disclosed form of less-than-bin replenishment, both touches occur in the store.

This design makes economic sense because it solves the space constraints that prevent large stocking runs associated with container refills, and is much more labor-efficient than picking P2G customer orders of SKUs in the center store, even with the extra touches. Furthermore, unlike the model of picking only high-speed SKUs in a G2P system, this design actually realizes a compelling return on the automation investment. Both high-speed SKUs (which may be stored in low-density totes) and low-speed SKUs (which may be stored in high-density totes) may be efficiently stored and picked from the G2P pick location.

One reason this design solves the central problem of economically fulfilling online orders in-store is the labor efficiency achievable using P2G picking of replenishment orders, which is much higher compared to P2G picking of customer orders, even when P2G picking of customer orders uses multiple order zone picking, as previously discussed. This difference in efficiency is due to several key differences between the two picking applications. Orders for items that were traditionally picked from the shelf in a P2G model (potentially slower) may now be fulfilled from the G2P pick side, thereby improving the efficiency of order fulfillment.

One difference is that the picking of all customer orders must be timed to be completed prior to the expected arrival of the customer or departure of the delivery vehicle to retrieve the order. Given the limited number of totes that can fit on a cart, and the relatively limited space available to store filled order totes awaiting transfer to the customer or vehicle, there is a small ability to bundle orders together for more efficient picking. As a result, it becomes necessary to send pickers on multiple trips through the same parts of the store each day to pick the order lines of different sets of orders as required by the completion deadlines. This, as with replenishment picking, results in fewer order lines per trip and significantly longer total travel distances to pick than if all order lines that need to be picked on a particular route could be picked in a single pass. Additionally, picking of customer orders must occur during times of the day when self-service customers are also shopping within those zones of the store, which slows down the pickers and requires significantly more travel time to traverse those long distances traveled that would be the case if no customers were present. In contrast, because replenishment picking is not bound by order deadlines at all, all replenishment order lines can be picked in batches in a single pass through the store, resulting in minimal total travel distance and maximum order line density. Furthermore, replenishment picking can occur at night when customers are not shopping. As a result, the speed at which replenishment pickers can travel this minimal distance is much faster than when picking customer orders during the day. For both of these reasons, the total travel time per order line picked when picking replenishment orders is much less than the total travel time when picking customer orders.

Another difference between these two applications concerns the average number of individual items picked per order line. With individual customer orders, most order lines are for a single individual item, and the average is typically around 1.2 or 1.3 individual items per order line. In contrast, with replenishment orders, to minimize replenishment frequency, all order lines typically require as many individual items as can fit into a secondary tote of a given size (within certain limits), and the average is typically at least 3 individual items per order line. This difference reduces the labor cost per individual item picked in two ways. First, because over time, both customer orders and replenishment orders require the same number of individual items for this set of NFPG SKUs to be manually picked, the number of order lines required for that picking is equal to the total number of individual items divided by the average number of individual items per order line. Thus, based on the above values, picking customer orders requires 2.5 times as many order lines as picking replenishment orders (3/1.2 = 2.5). Second, as previously mentioned, the second and subsequent individual items in an order line have a much lower incremental cost than the first individual item. In picking customer orders, only about 23% (0.3/1.3=0.23) of the individual items picked are these lowest cost individual items, while 67% (2/3=0.67) of the individual items picked for replenishment orders are the lowest cost individual items. Furthermore, even though there are more individual items to be removed from the shelf, replenishment picks take significantly less time to place those individual items into the order tote bins because the order lines do not have to be placed into any particular tote bin, but only into sections of a particular size. Thus, pickers can continuously place individual items from successive order lines into tote bins on the receiving shelf and replace the tote bins after they are filled. In contrast, when picking a customer order, the individual items from every order line must be placed into a specific order tote, so the picker must first access that tote (usually different for each order line) and then place the individual items into one of the bags within that tote, a much more time-consuming process.

Another difference between these two picking applications is that the "overhead" labor costs associated with setting up and handling picking carts for customer order picking are significantly greater than for refill order picking. One reason for this is that picking occurs at night when there are no customers in the aisles to be bothered or impeded by the picker, so the size and carrying capacity of the refill order carts can be significantly greater. More importantly, because every refill order tote receives many times as many individual items as a customer order tote, the total number of individual items that can be loaded onto a cart in a single trip is the tote carrying capacity of the cart in number of totes times the average number of individual items received by each order tote. Because both of these factors are significantly greater for refill order picking than for customer order picking, the difference is exacerbated as customer order picking requires many times more carts to be set up and moved to and from the store floor to collect a particular number of individual items.

For the reasons stated above, even including the additional (very low) labor cost of picking all of these individual items in the G2P system again significantly reduces the total labor cost of picking online orders for these NFPG SKUs compared to picking fully P2G customer orders because the labor cost of picking individual items to replenish the G2P system is much lower than picking those same individual items to fulfill customer orders. Of course, fresh and frozen packaged goods are still picked using P2G picking, but as explained above, these products have the lowest P2G picking costs to start with due to the localized concentration of these products in the store, and so the cost of picking the NFPG SKUs becomes the largest driver of the high cost of picking online orders.

It should also be noted that sorting all of these NFPG products within the G2P system offers four other very important advantages compared to the SKU velocity strategy:
• Because the automated system contains a great deal of accurate on-hand inventory data for NFPG SKUs that represent 90% of the packaged goods, there are many fewer stock-outs and fewer substitutes in the SKU density strategy than in the SKU velocity strategy.
By performing the majority of P2G individual product selection overnight rather than during the day while customers are shopping, this model eliminates this process as a source of inconvenience to customers.
The number of order tote boxes per customer order is significantly reduced compared to the multi-order P2G zone picking of most NFPG SKUs inherent in the SKU speed approach without the additional order consolidation labor. This reduction drives savings in both labor costs associated with distributing the orders and transportation costs associated with the delivery.
With an automated system picking all order lines except for fresh and frozen items, it becomes much more feasible to achieve service levels that include orders that are ready for picking or delivery quickly (e.g., within an hour).

It should further be noted that picking from and replenishment to a G2P system as described provides the following advantages: (1) Improved space efficiency, where higher SKU pick and SKU densities can be provided from the G2P system; (2) Improved labor efficiency, where operators can pick many more individual items from the floor per trip to the floor for G2P replenishment. As an example, picking from the floor for order fulfillment can result in 1.2-1.3 individual items per order line, whereas picking from the floor for replenishment in comparison results in more than two individual items per order line, where the higher number of effective individual items per operator step results in improved labor efficiency; and (3) G2P replenishment from the floor can be performed during non-peak shopping hours, resulting in an improved self-service customer experience. (4) This application offsets the need for upstream "break packs," which are breakups of containers at upstream distribution centers for shipment to stores, e.g., at low SKU sub-container counts; and (5) elimination of redundant order tote boxes with redundant bagging, storage, distribution, and cleaning; and (6) the G2P system is faster than manual picking, allowing for reduced order fulfillment cycle times, allowing "in-store" fulfillment while customers are shopping, and "same-time" delivery.

3B, the inventory transferred to the G2P storage (762) consists of the current day's persistent inventory, both replenished by batch picking from the store floor, plus inventory based on next day orders. Order fulfillment occurs in two models: self-service and e-commerce. In the "self-service" model, the customer selects or picks (252) the items that make up the order from the sales floor area and pays for the items, thereby fulfilling (254) each of the customer's orders in the "self-service" model. In the "e-commerce" model, the customer selects the items from a software application, which may be based on a computer, cell phone, or other device. The software application allows the customer to select items from the application for the order, which are fulfilled by the self-service retailer 116 from inventory picked (766, 768) primarily from within the G2P system. The selection of SKUs available to fulfill the same day orders (766) and next day orders (768) varies as described. The customer obtains or receives delivery of the order to fulfill the e-commerce order (770, 772) after the order is consolidated by the G2P system.

In the HD-MFC method, the store's own supply chain is utilized, for example, from floor shelves (760) to feed G2P machines (762) for online sales. One of the key issues with electronic commerce is selling online profitably. In the HD-MFC method, the labor required to pick individual items is done efficiently enough to fulfill the storage of the G2P system profitably, utilizing batch picking based on orders, as opposed to picking orders individually from the floor. In the HD-MFC method, inventory is not used in the classical sense, and storage capacity is allocated, as opposed to inventory allocation. Requisitions are made to look the same to the store site, as opposed to site replenishment with two separate replenishment streams of containers (748). One difference is the batch pick-and-replenish (762, 764) of a small G2P system in the MFC where there is much less or no sustained inventory, and the method places only what is needed for the next day's orders into the static G2P inventory at a specific level of today's availability of inventory (subject to substitutions). Here, periodically (e.g., daily), the system reallocates (762) totes and sub-totes in the G2P system to allocate static inventory for the next day, and also reallocates inventory based on orders to fulfill the next day's orders. In simple terms, the HD-MFC method provides small G2P machines in or adjacent to the store to allow the store to sell products to customers and make a profit on the sales. Here, the store floor provides a manual fulfillment system including pickers that fill the G2P system (762, 764) and the G2P system fulfills the orders (770, 772). Here, the HD-MFC method adapts the real world store in combination with the G2P system to extend the real world store and sell profitably online. Here, the self-service store is equivalent to becoming a distribution center overnight for each level of replenishment (764) of the G2P system for the next day (768). The store operates as a self-service store during the day (252) and uses the G2P system to pick the next day orders from the G2P store with a much larger product configuration (768) in addition to picking the current day's e-commerce orders from the G2P store with a smaller product configuration (766). Here, two different selections are available from the G2P system, a selection for the current day and a selection of the entire store basically for the next day. Here, persistent G2P storage is available for immediate fulfillment (770) for the current day from the G2P system. Further, in addition to the continuous G2P storage, the entire floor inventory that flows from the floor to the G2P system by overnight batch picking is available for next day immediate fulfillment (772) from the G2P system. Here, shelf-based floor storage serves as buffer storage for both the G2P system and the self-service floor. While all or most of the e-commerce orders are fulfilled by the G2P system, some same-day floor-based picking (774) may be provided, for example, picking fresh, frozen, and bulky items, where the bulky items are bulky but transportable, and order totes for these items may be stored in refrigerated or frozen storage in the G2P system until the order is fulfilled. Here, the G2P pick inventory is managed differently from the independent G2P fulfillment system. In the HD-MFC method, the Alphabot or any suitable G2P system is in fact a machine creating machine (i.e., the G2P system turns the entire store into an integrated machine). MFC's G2P allows stores to expand their capabilities: in addition to the always-existing purely manual P2G self-service fulfillment center, where the customer is the "P," stores that contain machines with a g2P system can also function as automated fulfillment centers for online orders.

In HD-MFC, the primary optimization goal of this method is to minimize the size of the G2P system (a more important feature with deployment going to the sales floor) while still essentially supporting a full grocery assortment. This goal is achieved by maximizing SKU density within the machine, leveraging a tote/sub-tote storage architecture. As an example, for a single store demand, most totes will store 6 or 8 SKUs, some totes will store 2, 3, or 4 SKUs, and only a few totes will be single SKU totes. One SKU is typically stored in only one sub-tote, and ideally a multi-location instance of one SKU should last for less than a day.

Because most of the secondary bins store relatively few individual items of slow SKUs, this method may often preclude bin replenishment, except for a few highest velocity SKUs that may be provided to replenish (778) the G2P system, for example. Bin replenishment is very effective in allowing large product assortments with cheap replenishment labor in large self-service stores, but requires a large number of low turnover storage spaces for slow SKUs. Thus, bin replenishment fundamentally works against the goal of minimizing G2P storage, especially given that online orders make up a small percentage of the total volume. While leveraging existing bin replenishment logistics to replenish G2P machines is very attractive and intuitive, this approach also drives a high-speed operation model to realize labor savings disproportionate to the number of SKUs in the G2P, and a centralized (hub-and-spoke) fulfillment model to aggregate demand to drive inventory turns and ROI on G2P automation investments. Both of these strategies are suboptimal compared to the high-density HD-MFC operating methods with distributed execution.

The HD-MFC's method of operation is to replenish the G2P system (764) with individual items that have been primarily manually picked (762) from store shelves during the nightly P2G batch picking process. While this approach may seem counterintuitive due to the additional touch of most of the individual items sold, the objective is to minimize total labor costs, not the number of touches. Compared to a manual, single-touch order picking process, replenishment batch picking is much more labor-efficient and therefore the cost of that additional touch is much lower due to four exemplary differences.

The pick density of batch picking is much higher than that of order picking because all the individual items for an entire day's replenishment can be picked in a single pass through the store, compared to the multiple waves required for order picking.

The number of individual items per order line is significantly (probably 2-2.5x) higher.

Pickers can move very fast without customers in the aisles.

Larger carts can be used without risking inconvenience to customers, reducing cart changes and associated fixed overhead labor costs (and by using AlphaRack sorting carts, some of this fixed overhead associated with setting up carts and installing totes is effectively eliminated).

The difference between same-day fulfillment 770 and next-day fulfillment 772 contributes to the effectiveness of this HD-MFC method because it allows a minimum amount of inventory to be stored in the system, and therefore the G2P system to be as small as possible. This effectiveness is achieved by selling off a daily stockpile of individual items picked for known next-day orders. There is a daily rotating pool of totes/sub-totes that is filled overnight (762) and emptied during the next day. Since all of the individual items needed for known next-day orders can be batch picked overnight and then picked to orders at the G2P machine prior to the order-by-order pick or ship deadline, the only individual items the Alphabot G2P system needs to maintain in the persistent inventory are those that are deemed necessary to fulfill not-yet-known same-day orders at the target service level. In effect, the batch picking is performed by a secondary sort to orders, using Alphabot as the G2P system as the sorting machine. Of course, depending on the amount of storage available, the system can always store more than this minimum amount of inventory, reducing replenishment costs by reducing the number of replenishment transactions required at a given movement rate and also increasing the average number of individual items per replenishment order line as they are picked.

Furthermore, when automated filling is applied, for example, as disclosed in U.S. Patent Application Publication No. US 2020/0039746, the entirety of which is incorporated herein by reference, and assembly of pick-ready multi-SKU totes at the DC to replenish MFCs, for example, as disclosed in U.S. Patent Application Publication No. 2018/01570793 and U.S. Patent Application Publication No. 2018/0247257, the entirety of which are both incorporated herein by reference, the total cost of replenishment with individual items is less than the current cost of replenishing store shelves with containers.

There may be certain categories of SKUs, such as perishables, bulky items, and frozen items (e.g., where space needs to be minimized), that may best be removed entirely from the persistent inventory so that same-day orders can also be fulfilled.

Because the HD-MFC method relies heavily on the ability of the store to maintain sufficient on-hand inventory in the store to support both self-service and online requests, it is worth working to ensure high quality in the execution of the store replenishment process already in place. For example, it seems very sensible to equip each store with an HD-MFC including an on-hand inventory checking robot, such as that provided by a Bossa Nova type robot or equivalent, and link that near real-time inventory data to the overnight replenishment plan of the present invention.

HD-MFC methods may have advantages over HV-MFC methods. In comparing the potential labor savings of the high-density method model with the high-speed method model, it can be recognized that there is a deviation in labor savings from automating the picking of high-speed SKUs in the HV model. This deviation arises from the extremely large reduction in P2G pick density after high-speed SKUs are removed from these pick routes. As an example, the cost per individual item of manual picking of low-speed items is much higher than the cost of picking all of the SKUs. If this increase is included in the calculation, then two touches of the HD-MFC to all or many of the individual items will likely result in labor savings at least equal to, and possibly greater than, one touch of every individual item in the high-speed model. While filling a G2P system requires less labor than replenishing shelves for batch picking, the difference is small, temporary, and insufficient to outweigh the very significant additional benefits of the HD-MFC model described below.

The above analysis may be applied to grocery products. When GM SKUs are included in an assortment that can be ordered online, the difference between batch picking and order picking favors the HD solution. For example, a relatively small increase in the size of the HD-MFC allows a sufficient assortment of GM products to be included in the persistent inventory to fulfill same-day orders. In contrast, very few GM SKUs (if any) exceed the velocity threshold to be picked G2P in the HV model. Moreover, picking these SKUs to order requires significantly more labor than batch picking for replenishment.

In addition to potentially lower sorting/replenishment labor costs, the HD-MFC process has four key advantages over the HV process:

First, the same labor savings can be achieved as with systems that are significantly smaller in size, resulting in lower capital expenditures, especially when the cost of retail floor space is included in this calculation.

The HD method removes the bulk of store employees picking individual items at the same time as customers shopping in the store, thereby removing a major source of dissatisfaction among self-service customers. Now, if the percentage of online orders exceeds a threshold of total store sales, self-service revenues will drop. The HV-MFC model is not at all effective at removing order pickers, as it still requires slower items to be picked from the floor for orders. Furthermore, the number of pickers continues to grow with demand, and the problem is exacerbated if the picking of slower SKUs for spoke stores is performed at the hub stores (which is the plan I envision). For example, the HV-MFC model does not suffer a large loss of store sales due to this impact on the self-service customer experience, causing a lower ROI from HV than from HD.

In the HD model, the sorting density of the order totes can be increased since the transfer of all individual items (except bulky individual items) from the product tote to the order tote occurs at the G2P sorting station, and the number of order totes per order is significantly reduced compared to the current indicators, while the HV-MHC model can significantly increase the number of order totes per order. This difference results in lower storage/distribution costs and, in particular, lower transportation costs for orders that are trucked to spoke stores or customer residences in the HD-MFC model. A separate order consolidation process to combine the contents of multiple totes for the same order may prove necessary to limit transportation costs in the HV-MHC model.

The HD-MFC model is simpler to operate for several reasons.

A very large portion of manual individual item selection is completely separated from customer acquisition or vehicle dispatch schedules, making it easier to meet service level commitments to customers and reducing the associated costs of dealing with schedule variability.

The HV-MFC model creates significant replenishment complexity. It requires continuous monitoring of the assortment (and assortment changes) which needs to be in the G2P system to consistently pick 80% of the individual items. This becomes a major challenge and certainly incurs additional labor costs to manage. In comparison, the assortment in the HD-MFC model is much more stable and essentially reflects most of the original assortment of the store, with the primary change being in the allocation of sub-carts based on changes in SKU velocity.

In the HD-MFC model, replenishment challenges are minimized because the demand signal from the store includes the majority of the volume online, excluding only a few highest speed SKUs. Given the ongoing complexity of a particular store to successfully replenish G2P, the HV model can prove difficult to get working correctly enough to achieve the target 80% coverage.

The overall simplicity of the HD-MFC method's model is reflected in the improved financial model, and implementing secondary tote boxes, e.g., as disclosed in U.S. Patent Application Publication Nos. 2018/0150793 and 2018/0247257, both of which are incorporated by reference herein in their entireties, automatic defragmentation, e.g., as disclosed in U.S. Patent Application Publication Nos. 2019/0047787 and 2020/0156871, both of which are incorporated by reference herein in their entireties, and the use of AlphaRack, e.g., as disclosed in U.S. Patent Application Publication No. 63/013,504, which is incorporated by reference herein in its entirety in addition to the previously incorporated references for both methods, improves the financial model.
High Density Motion Modeling Methodology HD-MFC is characterized by:
1. Objective: minimize size of structure, i.e. minimize number of totes in storage array2. Maximize SKU density by minimizing number of individual items and maximizing number of sub-totes per tote3. Abandon bin replenishment except for a few highest speed SKUs4. Replenish with individual items from store during overnight batch pick process5. Replenishment by batch pick is much more labor efficient than order picka. One pass through store versus many passesb. Pickers move faster with no shoppers in routec. Pick more individual items per order lined. Bigger carts, fewer trips can be used6. Also improves efficiency: automatic defrag7. In future, filling could be automated at upstream DC and MFCs replenished by sub-totes8. Difference between same-day and next-day ordersa. Minimum "static" (persistent) inventory needed for same-day ordersb. "Virtual" inventory concept: along with replenishment pick, individual items could be batch picked to fill next-day orders9. Special considerations for fresh, frozen, and bulky items a. Perishables: overnight batch-picked order line (virtual stock), same-day order line picked to order b. Bulky (but "transportable") items picked to order ("starter" totes)
c. Frozen goods are subject to space constraintsI. Typically picked to order using frozen storage in the MFC for order totes onlyII. Can be maintained in static inventory and treated as space permit like other packaged goodsFeatures of HD-MFC vs HV-MFC1. More scalablea. Smaller footprint and capital costb. MFC size has minimal impact on labor savings2. Same or lower operational costs3. Eliminates nearly all in-store individual item picking and inconvenience to customers4. Allows for faster same-day order completion times, improving customer experience5. Reduces stock-outs and substitutions, especially when tied to an ordering front endHD operating model (Figure 4) Features of "standalone" MFCs include:
1. Larger system height allows for smaller footprint 2. Integrated portal reduces capital expenditures and improves delivery times 3. Faster installation times 4. Less labor required in-store, minimizing disruption to operations 5. Expandable to automated remote distribution

3B, a flow diagram 800 for replenishment batch picking is shown. The flow diagram 800 is described with respect to structures and functions such as order management 808, Alphabot G2P system (MFc) 810, pick association application 812, and store personnel 814, however, any suitable structure or function may perform the process. For example, Alphabot G2P system (MFC) 810 may perform defragmentation and configuration of totes, sub-totes on the picking cart before the pre-configured totes including sub-totes are removed from the G2P system for batch picking. As a further example, instead of utilizing store personnel, robotic picking may be applied. As a further example, a pre-configured rack including pre-configured totes including sub-totes may interface with the G2P system and store personnel such that the picking cart is pre-configured and the entire cart interfaces with the G2P system, as opposed to introducing individual totes to and from the G2P system. These examples are intended to be illustrative only, and further examples may be provided by one skilled in the art from this disclosure. Order management 508 places next day orders, which may include forecasts for G2P non-orders (e.g., same day allocations) (516). Alphabot G2P system (MFC) 510 receives orders (518), generates a pick list for next day orders + same day order allocations (520), and provides the pick list and desired tote, sub tote types for each SKU (522). Pick association application 512 generates a pick walk (524). Store associates 514 construct pick carts including tote and sub tote (526), batch pick items from store shelves (528), and introduce the tote into the G2P system (530). Pick association application 512 provides SKU-tote-sub tote associations (532). The Alphabot G2P system (MFC) 510 provides delivery of empty totes and pickup of filled product totes (534) and updates inventory in the G2P system (536), while store personnel 514 remove empty totes (538) and introduce filled totes to the G2P system. The pick association application 512 determines if all pick walks are complete (540). If yes, the batch replenishment pick sequence is complete (542); if no, the cart is further configured (526) for further batch picking of items from the store shelves.

General rules and assumptions of replenishment may be applied. For example, SKUs with average daily sales above a threshold number of containers may be replenished with containers via a fill process. As a further example, SKUs with average daily sales below a threshold number of containers may be replenished with individual items via a replenishment sorting process or a sub-container fill process. As a further example, a reference replenishment calculation for the type and number of replenishments by SKU may be provided. As a further example, next day orders may be submitted to the Alphabot G2P system simultaneously or in batches based on a distribution schedule. As a further example, orders may not be modified by customers after they are submitted to Alphabot. These examples are intended to be merely illustrative and further examples may be provided by those skilled in the art from this disclosure.

Replenishment picking rules and assumptions may be applied. For example, replenishment picking may be completed before order picking can begin. As a further example, Alphabot G2P may provide a pick list consisting of all replenishment quantities by SKU. As a further example, the quota for same-day orders may be equal to the average quantity per day plus a buffer to achieve high service levels. As a further example, Alphabot G2P may provide the desired tote/sub-tote types by SKU. As a further example, the pick association application may generate a pick walk based on the store's planogram. As a further example, the pick association application may track the completion of the pick walk. As a further example, an employee may remove empty totes from Alphabot G2P to configure a pick cart. As a further example, Alpharacks may be used as a removable part of G2P to enable higher tote introduction rates and further reduce labor as described. These examples are intended to be illustrative only, and further examples may be provided by one of ordinary skill in the art given this disclosure.

Now referring to FIG. 4, an exemplary store site format 410 utilizing the disclosed method is shown. The site format 410 resides on a particular site 416, which may include an inventory managed by an inventory management computing device 420, and a host store 418 with a receiving area 422, a storage area 424, and a sales floor 428. The host store 418 may be located along a parking lot 426, and a G2P system 430 is deployed within the parking lot 426. The system 430 may be sized to serve the orders of the host store 418. The system 430 is located at approximately 10,000-12,000 totes, but due to the high SKU density, may be appropriately sized to stock substantially all of the host store 418's non-frozen packaged goods assortment.

The operating model of site 410 sets an order volume threshold below which the site performs entirely manual fulfillment and installs system 430 after order volume reaches this threshold. This threshold may initially be about 200 orders per day. Alternatively, 500 orders per day is a relatively high single store volume today, but demand is expected to continue to grow.

While locating the G2P system 430 within the store 418 may be an option, the site 410 is configured to build the system 430 as a standalone machine that is installed in an area of the parking lot 426 near the side of the store 418 (e.g., the grocery side of the store). Note that not all stores include a room for the individual item selection system inside the store, but all stores have parking. Customer access portals 432 may span the length of the structure on both sides, with parking spaces directly in front of each portal. At one end, between the store and the remote automated distribution unit, there is a truck dock 434 for loading order totes for truck ferry transport. This parking deployment strategy has several characteristics:

The machines can be tall: typically about 35 feet tall, but for very busy stores requiring more storage and/or throughput, they may go up to 45 feet. Scaling vertically gives more throughput by adding layers of deck connections at a much lower incremental cost than expanding horizontally by adding more aisles. Scaling vertically also minimizes the footprint, making it very feasible to place in a parking lot. A standard footprint would probably be about 130 feet long by 30 feet wide, totaling 4,000 square feet. There could be one basic 3-aisle topology that could be modified to various heights and aisle lengths to meet throughput and storage requirements.

Attaching customer acquisition portals 432 directly to the sorting system maximizes service levels, i.e. minimizes delivery wait times. For example, a 130 foot length would support at least 20 portals. This would theoretically yield a throughput of up to 120 orders per hour, even with a dwell time of 10 minutes per order. A more customer friendly drive-thru option may also be provided.

The system 430 may be classified as a machine rather than a building designed for general human occupancy, which by its much larger size reduces the provision of parking spaces by a relatively small margin due to reduced demand for parking spaces.

The system 430 can be erected in a parking lot much more quickly and at a lower overall cost to the retailer than in an existing store. The design can also be easily adapted for remote automated dispense (RAD) applications, where any RAD can be served from any store at any time. The latter feature can prove useful in balancing the workload across a network of stores and RADs.

Customer order lines for room temperature and refrigerated packaged goods may be picked by the G2P system 430 at room temperature workstations. Optionally, picking of pre-packaged fresh items (bar coded and priced) may be provided and supported, but some items may be picked at the store, e.g., frozen items may be picked at the store because they are the lowest cost SKU to pick in the store. Here, frozen and usually fresh products (and only those products) may be picked in the store to customer orders. Customer orders for frozen SKUs may be picked into refrigerated totes and then introduced (434) into the Alphabot system for placement in refrigerated storage or even room temperature storage awaiting the customer's arrival.

The bot travel rail 434 may connect the system 430 and the store 418 so that the bots can receive incoming filled customer order totes and refill order totes and deliver empties to employees through a single path of static workstations (SWS) 438 in the store. These workstations may be as described in U.S. Patent Application No. 16/642,119, entitled "SYSTEM HAVING WORKSTATION WITH TOTE RETENTION AND RELEASE MECHANISM," filed on January 14, 2020, which is incorporated herein by reference in its entirety.

The SWS 438 may be dual level like a wall of totes since half of the tote transfers are empty order totes distributed to pickers while the other half are filled customer order totes/replenishment order totes being introduced (alternatively to a dual level SWS these two functions may be performed on both sides of the aisle). The aisle may contain two zones, frozen and refrigerated (or possibly frozen and room temperature). The frozen area is where the refrigerated totes are loaded. The refrigerated (or room temperature) zone is where a limited amount of filling is performed for the highest rate of refrigerated or room temperature SKUs being replenished by containers. The majority of the replenishment pick inventory is introduced into the system in totes of multiple SKUs filled by replenishment pick. One must think about the introduction of AlphaRack and the design of these picking carts.

Refrigerated tote handling and automated tote defragmentation may be provided using a Cartesian robot in system 430 as disclosed in U.S. Patent Application Publication No. US2020/071076, entitled "Tote Handling for Chilled or Frozen Goods," published on March 5, 2020, and U.S. Patent Application Publication No. US2019/0047787, entitled "UNIVERSAL GRIPPER FOR TOTE AND SUB-TOTE TRANSPORT," published on February 14, 2019, both of which are incorporated herein by reference in their entireties.

Incorporated materials

As previously discussed, the present technology may be used in conjunction with order fulfillment and automation based technologies, at least some of which are disclosed in published applications previously incorporated by reference and at least some of which are provided below.

US Patent Application Publication No. 2017/0313514 discloses a system including workstations, decks, and storage locations, as shown in Figures 5 and 6. Figure 5 shows an exemplary configuration of workstations 5500, with at least three workstations 5500 located at each storage level, while in other aspects, any suitable number of workstations may be located at each storage level. The workstations 5500 at different levels may be vertically offset from one another, such as stacked one above the other or stacked in a staggered arrangement. In one aspect, each workstation 5500 is communicatively connected to two travel decks 5550A, 5550B, while in other aspects, each workstation 5500 may be communicatively connected to any suitable number of travel decks. In one aspect, a travel deck 5550A, 5550B may correspond to each storage level, while in other aspects, the travel decks 5550A, 5550B may correspond to a common storage level (e.g., there are two or more travel decks associated with each storage/sorting level). In another aspect, there may be a tower located on or otherwise connected to (or disposed within) the travel deck (or aisle), which communicatively connects one or more of the travel decks 5550A, 5550B (or aisles) of different storage levels to and from a travel loop that includes another tower, such that the bot 5100 (FIG. 6) may traverse between the stacked travel decks 5550A, 5550B (or aisles) to any desired/predetermined level of the storage structure. The workstation 5500 is configured to accommodate a picker 5520 that transports one or more individual items from a tote (e.g., P tote) on one of the bots 5100 to a "place" location in a tote (e.g., O tote) on another one of the bots 5100. The workstations 5500 may be arranged in multiple elevations, with human or robotic pickers removing individual items from product totes (P totes) and placing the individual items on either an order tote (O tote) or a mobile robot, depending on the system configuration, in a manner substantially similar to that described above. The workstations 5500 are arranged on each traffic deck level so that the bots 5100 on each traffic deck can access the workstations 5500. In the exemplary embodiment shown in FIG. 5, six traffic deck levels are shown, with two levels each connected to a common workstation 5500. However, in other embodiments, any suitable number of traffic deck levels may be connected to the common workstation 5500.

Figure 6 shows a workstation 5500. Each of the transport lanes 5501, 5502, 5503, 5504 includes a respective entrance and/or exit 5500E in communication with the respective travel deck 5550A, 5550B. As can be seen in Figure 54A, the transport lanes 5501, 5504 include an entrance/exit 5500E in communication with the travel deck 5550B, while the transport lanes 5502, 5503 include an entrance/exit 5500E in communication with the travel deck 5550A. The transport lanes 5501-5504 include rails WRR. As can be seen in Figure 6, the lift towers 5190TWA-5190TWD connect the stacks of transport lanes to each other. As an example, the lifting towers 5190TWA and 5190TWB connect the transport lanes 5503 and 5504 so that the bot 5100 can cross between the transport lanes 5503 and 5504. The lifting towers 5190TWC and 5190TWD connect the transport lanes 5501 and 5502 so that the bot 5100 can cross between the transport lanes 5501 and 5502.

In one aspect, one or more of the transport lanes 5501-5504 and towers 5190TWQ-5190TWD may be angled (e.g., tilted or inclined) relative to the travel decks 5550A, 5550B, and operator platform 5510 so that the P and O transport boxes are angled as they are presented to the picker 5520 by each P and O bot, and the picker 5520 can see and access the P and O transport boxes for picking and placing individual items from the picking/placement locations defined by the towers 5190TWQ, 5190TWC adjacent the sorting station 5530. In other aspects, the transport lanes 5501-5504 and towers 5190TWA-5190TWD may have any spatial relationship with the sorting station 5530 and/or the travel decks 550A, 5550B to present the transport boxes to the picker 5520 in any suitable spatial orientation.

In one aspect, the transport lanes 5501-5504, the lift towers 5190TWA-5190TWD, and the sorting station 5530 have a symmetrical structure, along with the paths and locations of the independent product bots (P bots) and order bots (O bots). In this aspect, there may be lateral (in the direction 5599) symmetry such that there is a symmetrical arrangement. For example, the symmetrical arrangement may be such that the P bot carrying the P tote box is located on the right side of the workstation 5500, while the O bot carrying the O tote box is located on the left side of the workstation 5500. In another aspect, the P bot and the P tote box may be on the left side of the workstation 5500, while the O bot and the O tote box may be on the right side of the workstation 5500.

In one embodiment, there are transport lanes dedicated to the entrance and exit of the bot flow for both P bots and O bots. For example, the flow of bots to the sorting station 5530 may be such that the bots move from a lower transport lane to an upper transport lane, or in other embodiments, from an upper transport lane to a lower transport lane. For example, when the bots move from the lower transport lane to the upper transport lane, the P bots carrying the individual items to be sorted enter one or more lower/lower transport lanes 5501 and traverse the tower 5190TWC toward one or more upper transport lanes 5502 so that the individual items can be sorted when the P bots exit the workstation using one or more upper transport lanes 5502. Similarly, the O bots carrying the O tote boxes in which the individual items are placed enter one or more lower/lower transport lanes 5504 and traverse the tower 5190TWA toward one or more upper transport lanes 5503 so that the individual items can be placed when the O bots exit the workstation using one or more upper transport lanes 5503. In other aspects, when towers 2190TWA-5190TWD are employed to route bots past one another, such as when bots enter and exit common transport lanes 5501-5504, the time at which a bot enters a workstation may be determined so that the bot can enter and exit from both the upper transport lanes 5502, 5503 and the lower transport lanes 5501, 5504. In the above example, the flow of P bots carrying P transport boxes and the flow of O bots carrying O transport boxes are generally both in a common direction, such as both in the direction of arrow 5598 from the lower transport lane to the upper transport lane, or both in the direction of arrow 5597 from the upper transport lane to the lower transport lane. However, in other aspects, the flow of one or more of the P bots and O bots may be in the direction of arrow 5597 from the upper transport lane to the lower transport lane. For example, the flow of P bots and P transport boxes may be in direction 5598, while the flow of O bots and O transport boxes may be in direction 5597, or vice versa.

In one aspect, both sides of the workstation 5500 (e.g., product side and order side) include lift towers dedicated to flow directions. For example, the lift tower 5190TWC on the product side of the workstation 5500 may be dedicated to the upward flow of bots, while the lift tower 5190TWD on the product side of the workstation 5500 may be dedicated to the downward flow of bots, or vice versa. Similarly, the lift tower 5190TWA on the order side of the workstation 5500 may be dedicated to the upward flow of bots, while the lift tower 5190TWB on the order side of the workstation 5500 may be dedicated to the downward flow of bots, or vice versa. The dedicated flow of bots per tower 5190TWA-5190TWD on the order or product side, respectively, of the workstation 5500 creates an up-down flow loop in one or more of the directions 5597, 5598 between the levels of transport lanes 5501-5504 on the order and product sides, respectively, of the workstation 5500, for example, in a manner substantially similar to that described above. As previously described, although only two transport lanes are shown stacked one on top of the other on each side of the workstation, in other aspects each side of the workstation may include any suitable number of transport lanes stacked one on top of the other, such as more or less than two transport lanes. If the product side and/or order side of the workstation 5500 provides three or more transport lanes stacked one on top of the other, the towers 5190TWA-5190TWD may include intermediate entrances and exits that allow bots to enter/exit the tower from intermediate transport lanes located between the top transport lane 5502 and the bottom transport lane 5501 of the stack of transport lanes.

7A, referring to U.S. Patent Application Publication No. US2018/0134492, illustrates a representative conceptual interior layout of a store 300 and how each of the areas of the store 300 relate to one another. In particular, FIG. 7A illustrates a shopping area 302, an automated fulfillment area 304, a delivery fulfillment area 308, and a pick-up area 310. Although the different areas depicted in FIG. 7A are depicted in a single plane, these areas may be divided into multiple floors of the store 300. During the business hours of the store 300, all transactions occur through one or more of these areas. In accordance with an example embodiment of the present invention, a customer utilizes an entrance 306 to enter (402) and exit (404) the shopping area of the store 300. After entering within the shopping area 302 of the store 300, the customer may order items to be fulfilled by automated order fulfillment, as described in detail herein, and may shop for non-substitutable items within the non-substitutable item fulfillment area of the store.

Customer orders fulfilled by automated order fulfillment are processed by an automated system in the automated fulfillment area 304, as described in detail herein. When the automated order fulfillment is completed, the automatically selected items are provided (406) to the delivery fulfillment area 308, as described in detail herein. Similarly, when the customer completes the selection of non-fungible items in the shopping area 302, the customer provides the items (408) to the delivery fulfillment area 308, as described in detail herein. For example, the customer may place a tote box or basket containing the items in the delivery fulfillment area 308 through a window. At the delivery fulfillment area 308, the items provided (406) from the automated fulfillment area 304 and the items provided (408) from the shopping area 302 are combined into a single order for delivery (410) to the customer, as described in detail herein.

Continuing with FIG. 7A, the store 300 may include a receiving area 310 for receiving merchandise from various suppliers and/or manufacturers. The receiving area 310 may be included in the "back end" of the store not seen by customers. When merchandise is delivered to the receiving area 310, it is identified as a non-fungible item for storage in the shopping area 302 or a fungible item for storage in the automated fulfillment area 304. The non-fungible items are diverted (414) and stored in the shopping area in a manner that provides fulfillment of the non-fungible items. Similarly, the fungible items are diverted (416) and stored in a manner suitable for automated order fulfillment (e.g., stored in totes, placed on storage racks).

7B shows a more detailed view of the internal structure of the store 300 as described with respect to FIG. 7A. In particular, FIG. 7B shows a detailed view of the shopping area 302, the delivery fulfillment area 308, and a floor plan of the automated fulfillment area 304, and how these areas relate to each other. The shopping area 302 includes the entry and exit points 306, the simulated market 600, and the opening 408 to the automated fulfillment area 304, as shown in FIG. 7B. The simulated market 600 includes a wall of order screens 602, a number of physical shelves 604 and display cases 606, and a number of shopping terminals and checkout kiosks 619. As will be appreciated by those skilled in the art, the simulated market 600 can include any combination of the elements shown in FIGS. 7A-7C. Additionally, FIG. 7B shows the delivery fulfillment area 308 of the store 300. The delivery fulfillment area 308 includes a number of transfer stations 611 to which completed orders of merchandise are delivered for collection by customers.

7C shows a more detailed view of the automated fulfillment area 304, a basic view of the delivery fulfillment area 308, and the shopping area 302, and how these areas relate to each other. The automated fulfillment area 304 includes a storage rack system 613 configured to hold inventory totes accessible by the robot and further configured to allow the robot to extract the inventory totes and deliver the totes to a picker at a picking workstation 614 for automated order fulfillment. In accordance with an example embodiment of the present invention, the delivery fulfillment area 308 includes a consolidation area in which items from the automated fulfillment area 304 and items from the shopping area 302 are combined and consolidated into order totes for delivery to customers at a transfer station 611. As will be appreciated by one of ordinary skill in the art, this consolidation can occur within the same physical space as the automated fulfillment area 304 or within a different physical space.

In accordance with an example embodiment of the present invention, the store 300 of the automated service model 100 includes a "front end" that includes an entrance lobby, a non-fungible goods shopping area 302, and associated work areas. As will be appreciated by those skilled in the art, the front end is not necessarily located at the front of the store 300 or on the first floor of the store 300. A majority of the floor space within the shopping area 302 is devoted to a non-fungible goods market (produce, fresh produce, and other non-fungible goods) and associated work space, which may be the center of the store 300 from the customer's perspective. The shopping area 302 includes "non-fungible" goods such as produce, meat, seafood, many cheeses (mostly random weights), prepared foods, flowers, bakery, and prepared foods. Typically, non-fungible items are sold from display fixtures or stands 606 using three different pricing methods, including but not limited to "random amount" (fungible items with price bar codes), random weight (unpackaged items, especially produce, priced by item weight), and random number (unpackaged items priced based on number of individual items). These non-fungible items can also be sold at a service counter, which provides customers with more opportunities to customize ordered products according to personal tastes and preferences.

In accordance with an example embodiment of the present invention, the shopping area 302 of the store 300 is similar in appearance to a perimeter department in a conventional self-service grocery store, with technological enhancements associated with an automated service model to improve customer convenience and reduce the retailer's operating costs. The technological improvements to the shopping area 302 relate primarily to the manner in which customers shop for merchandise and exchange funds for those merchandise. One such technological improvement is the implementation of shopping terminals utilized in conjunction with the automated service model. Shopping terminals are devices utilized as the primary interface by customers to select, scan, enter, and/or store items for orders placed during a shopping trip, including the exchange of funds for the order. In particular, shopping terminals may be utilized to order both fungible items (as selected by automated order fulfillment) and non-fungible items within the fulfillment of non-fungible items.

As will be appreciated by one of ordinary skill in the art, the shopping terminal can be any device configured to identify (e.g., by scanning, photographing, etc.) a particular item to be added to a shopping list. For example, the shopping terminal can be a portable scanning device or one or more fixed touch screens located within the shopping area 302.

8A, 8B, 8C, and 8D, with reference to U.S. Patent Application Publication Nos. US2018/0150793 and US2018/0194556, illustrate an example embodiment of the present invention in which a customer order for fungible items is fulfilled by an automated system in an automated fulfillment area 204. When an automated fulfillment order is completed, a tote box 1232 containing fungible items picked by the automated mobile robot 122 and picker 1234 is provided (e.g., via path 408) to a delivery fulfillment area 208. Similarly, when a customer completes picking non-fungible items in the shopping area 202, the customer provides the goods (e.g., via path 410) to the delivery fulfillment area 208. According to an example embodiment of the present invention, the delivery fulfillment area 208 includes a consolidation area 240 in which merchandise from the automated fulfillment area 204 and merchandise from the shopping area 202 are combined and consolidated into order totes 1232 for delivery to customers at one or more transfer stations 1242.

In the consolidation area 240 of the delivery fulfillment area 208, fungible items provided from the automated fulfillment area 204 and non-fungible "perishables" provided from the shopping area 202 are combined into a single order for delivery to a customer at the transfer station 1242. In particular, the consolidation area 240 includes a merge module that combines individual items picked from the automated fulfillment area 204 with individual items picked from the shopping area 202, and the combination is placed at one or more transfer stations 1242 where the items are dropped off. The combined individual items from both areas 202, 204 form a delivery batch (e.g., one or more totes 1232 of items), and the automated mobile robot 122 transfers the completed delivery batch to the transfer station 1242, which receives the delivery batch and stores the delivery batch at a designated location until the customer arrives to pick up the delivery batch.

According to an example embodiment of the present invention, during consolidation, the multiple automated mobile robots 122 are tasked with picking up totes 1232 of goods from their respective zones 202, 204 and transferring those totes 1232 to the merge module of the consolidation zone 240. Based on the number of goods, one or more of the multiple automated mobile robots 122 or one or more new automated mobile robots 122 can pick up the batch of deliveries and transfer the batch to the appropriate transfer station 1242. Each of the tasks as related to FIG. 8A is performed within a delivery operating mode (e.g., deliver goods from the shopping zone 202, deliver goods from the automated fulfillment zone 204, deliver the completed batch of deliveries to the transfer station 1242, etc.) that includes various task requests provided to each of the automated mobile robots 122 performing each specific task. As will be appreciated by those skilled in the art, this consolidation can occur within the same physical space as the automated fulfillment zone 204, the delivery section 208, or within a different physical space.

8B illustrates an exemplary diagram of the delivery fulfillment area 208 and its conceptual relationship to the automated fulfillment area 204 and the shopping area 202. In accordance with an example embodiment of the present invention, the delivery fulfillment area 208 includes a number of transfer stations 1242 configured for customers to retrieve their orders. The transfer stations 1242 are configured to deliver goods directly to customers or customer vehicles in a variety of ways.

In accordance with an example embodiment of the present invention, the replenishment area 206 of the automated store 300 is configured to receive shipments of merchandise from various suppliers and/or manufacturers. The replenishment area 206 is contained within the "back end" of the store, which is not typically seen by customers. FIG. 8C illustrates an example diagram of the replenishment area 206 and its relationship to other areas of the automated store 300. In particular, FIG. 8C illustrates the replenishment area 206, including a docking area that receives containers of merchandise (e.g., via trucks). In accordance with an example embodiment of the present invention, the containers of merchandise may be received as pallets 1250 of containers or as portable racks of totes 1232 with the merchandise stored therein. The portable racks 1252 of totes 1232 may be received from a distribution center designed to implement with the automated store 300. Initially, regardless of the shipping method, when the merchandise is delivered to the replenishment area 206, the merchandise is identified as a non-fungible item for storage in the shopping area 202 or a fungible item for storage in the automated fulfillment area 204. Based on the determination of fungible or non-fungible items, the received items are assigned to the designated areas accordingly. In particular, non-fungible items are routed (e.g., via path 406) to shopping area 202, and fungible items are routed (e.g., via path 404) and stored in a manner suitable for automated order fulfillment (e.g., stored in totes 1232 and placed on storage racks 1230).

As will be appreciated by those skilled in the art, depending on whether the goods are received by a pallet of containers 1250 or a portable rack of totes 1252, the goods are received into the inventory of the automated fulfillment area 204 by different methodologies. In accordance with an example embodiment of the present invention, the replenishment area 206 includes a filling station 1254 configured to replenish goods into the automated fulfillment area 204, as shown in FIG. 8D. The filling station 1254 may be utilized to replenish goods received from manufacturers, suppliers, and customer returns. The filling process includes transferring the products and/or customer returns from the pallet of containers 1250 into totes 1232 stored in the storage racks 1230 of the automated fulfillment area 204.

In operation, the automated mobile robot 122 is configured to assist and/or perform various operations throughout the automated store 300. Each of the various operations is performed by assigning the automated mobile robot 122 (e.g., via a central controller) to one or more operation modes. The operation modes include, but are not limited to, a replenishment mode, a de-fragmentation mode, an order fulfillment mode, and a delivery mode. The replenishment mode includes receiving individual items and placing the individual items in designated storage totes and/or storage locations in the storage racks 1230, the de-fragmentation mode includes organizing the totes 1232 and consolidating sub-totes stored in the totes 1232, the order fulfillment mode includes retrieving order totes from the storage racks 1230 and delivering the order totes to the delivery zones 208, and the delivery mode includes receiving delivery chunks and transporting the delivery chunks to designated locations of the retrieved item transfer stations 1242. In accordance with an example embodiment of the present invention, each of the different operation modes is performed by the same design of the automated mobile robot 122. In other words, a single automated mobile robot 122 is capable of performing the tasks required by each of the operational modes without modification.

In accordance with an example embodiment of the present invention, the tote boxes 1232 are interchangeable and designated with different identifiers for the automated mobile robot 122. That is, the tote boxes 1232 are structurally the same and therefore interchangeable in the tasks in which the tote boxes 1232 may be utilized based on the designation associated with the tote boxes 1232. The tote boxes 1232 are designated based on their capabilities as well as the operational mode in which they are utilized. In particular, the interchangeable tote boxes 1232 may be designated as empty storage tote boxes when empty (e.g., no products are contained therein), as storage tote boxes 1232 or product tote boxes 1232 when storing individual products (e.g., inventory), as order tote boxes when storing individual products for customer orders, or combinations thereof. In operation, the system 100 provides the designation, which assists the automated mobile robot 122 in identifying which tote box 1232 should be utilized for which operational mode. For example, if the automated mobile robot 122 is instructed to pick up and empty totes 1232 as part of an operational mode, the automated mobile robot 122 knows or is instructed to locate totes 1232 designated as empty totes 1232.

In accordance with an example embodiment of the present invention, the centralized controller can identify and track all of the automated mobile robots 122, totes 1232, their respective designations in the system (e.g., operational mode or tote designation), and the location of individual items within each sub-tote contained within each tote bin 1232. The identification of the locations for all of the automated mobile robots 122 and totes 1232 can be further utilized by the centralized controller when assigning the automated mobile robots 122 to different operational modes. In particular, the centralized controller can identify all of the automated mobile robots 122 located within a particular area and instruct those automated mobile robots 122 to perform a particular operational mode within that area. The centralized controller attempts to horizontally load the automated mobile robots 122 to ensure that all required store 300 operations are completed with the fewest number of automated mobile robots 122.

When the centralized controller wishes to assign an operational mode to one or more automated mobile robots 122, the centralized controller sends a work request to one or more automated mobile robots 122 instructing them which task to perform according to the operational mode. In particular, the work command includes instructions regarding a destination and picking or placing a tote at the destination. Additionally, the work request may include specifying one or more tote boxes 1232 to utilize during the operational mode, and an origin/destination location for the one or more tote boxes 1232. As will be understood by one skilled in the art, although the present invention is described with respect to providing instructions, requests, and the like, via a centralized controller, some or all of the control elements may be distributed throughout the system, including logic stored within the automated mobile robots 122 themselves.

In accordance with an example embodiment of the present invention, the replenishment mode involves the automated mobile robot 122 navigating itself through the storage rack 1230, delivering partially filled or empty totes 1232 to a filling station, receiving totes 1232 (e.g., storage totes or product totes) containing goods for replenishment, and/or transporting refilled totes 1232 of goods to a storage location within the storage rack 1230. As will be appreciated by those skilled in the art, the totes 1232 are interchangeable and may be utilized interchangeably within the operational mode, such that a product tote may be utilized to replenish, store, and deliver products to a workstation for order fulfillment. A particular tote designation relates to the function the tote is currently performing, based at least in part on the contents of the tote. When operating in the replenishment mode, the automated mobile robot 122 receives multiple task requests regarding where to traverse to receive the tote 1232 of goods for replenishment and where to traverse to place the refilled tote 1232 of goods within the storage rack 1230. As will be appreciated by those skilled in the art, the work request repeats these steps for each new bin 1232 for refilling.

Furthermore, depending on the manner in which goods are provided in the replenishment area 206, the automated mobile robot 122 may perform the same mode of operation in different ways influenced by various task requirements. For example, the mobile robot 122 may be directed to traverse different areas in the replenishment area 206/automated fulfillment area 204 when receiving goods originating from a container pallet 1250 than when receiving goods originating from a moving rack 1252 of a tote box 1232. FIG. 8C illustrates how the initial location for receiving the tote box 1232 for replenishment may vary based on the dispatch method. In particular, when goods are received via a container pallet 1250, the container pallet 1250 is unloaded and transported to a filling station 1254, either by an automated process or by a human operator.

9, referring to US Patent Application Publication No. US2018/0247257, illustrates an exemplary system 10 for performing steps according to aspects of the present technology. As seen in FIG. 9, as described in more detail below, a pallet-loaded container 12 of goods is received at one or more regional distribution centers (RDCs) 14, which deliver a mix of pallet-loaded containers 16 of goods to a market distribution center (MDC) 18, which fills and stores similar individual goods in sub-totes 24 of various sizes and delivers a tote containing each of the mixed sub-totes 20, 22 to a market 26. Alternatively, shipping to stores or markets in totes may be performed directly from the distribution center without a market distribution center, or the functions of the regional and market distribution centers may be combined. In addition to allowing sufficient scale to provide automated replenishment, market distribution centers also reduce the cost of transporting individual items in totes and sub-totes to local, e.g., metropolitan, areas. More efficient dispatch of individual items in densely packed containers on pallets can be maintained between regional and market distribution centers. Market distribution centers further provide the ability to store a large selection of items not regularly stored at the market that customers may order to be delivered to the market in the next rapid replenishment delivery.

10A and 10B, referring to U.S. Patent Application Publication No. US 2018/0341908, illustrate a portion of an automated self-service retail store 1100. The store 1100 includes a shopper-accessible area 1102 that includes a number of aisles 1104 containing tote bins 1106 from which a shopper 1110 can select individual items for placement in a shopping cart. The aisles 1104 may include flat-panel monitors 1112 that illustrate the individual items in the tote bins 1106. The flat-panel monitors may be displays or other input terminals, such as interactive touch screens, that provide information regarding the prices and items in the tote bins below the flat-panel monitors.

The store 1100 may further include a product storage and replenishment area 1122 located above the shopper accessible area 1102. The product storage and replenishment area 1122 stores the tote boxes 1106 in a storage rack 1128 for refilling the tote boxes 1106 in the shopper accessible area 1102. The storage rack is then connected to a rail along which the mobile robot 1124 moves. For example, when a tote box in the shopper accessible area 1102 is empty, the tote box 1106 is automatically delivered to the shopper accessible area 1102 by the mobile robot 1124. At the same time, the product information on the flat panel monitor above the tote box is updated. The robot 1124 may replenish the empty tote box 1106 with the same product or a different product. A central material control system (MCS) 1114 controls the mobile robot and also updates the information on the tote box. The MCS 114 may control when and what the tote bins 1106 in the shopper accessible area 1102 are replenished with. The MCS may also track items removed from the tote bins 1106 by shoppers 1110, as described below.

10A and 10B show a single shopper accessible area 1102 located below the product storage and replenishment area 1122. However, in further embodiments, the product storage and replenishment area 1122 may be below or at the same level as the shopper accessible area 1102. Additionally, in further embodiments, there may be multiple levels of shopper accessible areas 1102, each of which is replenished from totes stored in the product storage and replenishment area 1122.

10A and 10B show a system in which inventory is maintained in a tote 1106 on the shopper accessible level 1102. However, in further embodiments, the shopper accessible level 1102 may not store inventory. Instead, the shopper accessible level may include a station (shopper station) and a display screen 1112. In this embodiment, the shopper may select their desired items from the display screen, and a tote containing those items is delivered to the user by the mobile robot 1124. Once the shopper has selected their desired items from the tote 1106, the tote 1106 may be carried away by the mobile robot 1124, and an additional tote may be delivered to the shopper 1110 with the shopper selected items. The shopper selected items may be delivered to the user in tote bins held by multiple different robots, with the movement of the robots being coordinated by the MCS 1114.

Referring to U.S. Patent Application No. 17/236,082 (which claims priority to U.S. Provisional Patent Application No. 63/013,504), FIG. 11 shows a top view of an exemplary system 2250 utilizing widthwise insertion and extraction from a storage structure, and both widthwise and lengthwise insertion and extraction from boxes on a shipping truck. The system 2250 has a storage structure 2256, a dock staging area 2258, and tracks 2260, 2262. The storage structure 2256 has a rack 2264 that may have rails and verticals that allow the bot 2150 to traverse vertically (between levels) on support rails along an aisle or from aisle to aisle. The storage structure 2256 has a traveling deck 2266 that allows the bot to move horizontally between aisles. The collapsible rack 2100 is shown being removed from or inserted into the rack structure 2264 widthwise. On the other hand, the folding rack 2100 may be composed of two racks or more racks, which are combined in a single folding rack to support a configuration in which more than two totes are folded as shown. The folding rack 2100 is shown being removed or inserted in the width direction from the track 2260 and in the length direction from the track 2262. On the other hand, the combination of the length direction and width direction racks may be provided in a foldable, folded, or open/unfolded configuration. The automatic motorized robot (AMR) 2206 may be utilized to transport the rack 2100 to and from the storage structure, and the automatic motorized robot (AMR) 2206 may be an automatic robot that works autonomously. On the other hand, the automatic motorized robot (AMR) 2206 may be a human-operated power-assisted transport drive, as well as an automatic vehicle, an automatic fork truck, or other suitable drive adapted to transport the rack 2100 from destination to destination. Alternatively, the rack 2100 may be transported manually, in which case the automated motorized robot (AMR) 2206 would not be provided. In the illustrated embodiment, the rack 2100 is folded and inserted widthwise into the track 2260 and lengthwise into the track 22622. Alternatively, the rack 2100 may be partially folded, e.g., the bot 2150 is intended to be transported as shown. In the illustrated embodiment, the rack 2100 may be short-circuited widthwise or moved linearly directly to/from the rack structure 2256 and then transported lengthwise as shown, or widthwise from/to the tracks 2262, 2260.

16/831,468, FIG. 12 shows a schematic plan view of an order fulfillment system 810. The order fulfillment system 810 includes a multi-level tote storage and retrieval structure 820, room temperature and refrigerated autonomous robotic vehicles or robots capable of operating in room temperature and refrigerated environments 822, 824 configured to pick, transport, and place one or more totes in the order fulfillment system, and a combination of different individual items reflecting a fully or partially fulfilled order, which may be on another of the autonomous mobile robots at a workstation, from a tote bin on one of the autonomous mobile robots, e.g., a product tote bin containing multiple common individual items to be picked, to a placement location. the order fulfillment device, room temperature 826 and refrigerated 828 workstations configured to accommodate pickers (human, automated, or otherwise) that transport one or more individual items to an order tote having ... The tote box storage and retrieval structure 820 may have a room temperature storage and retrieval structure 838 and a refrigerated storage and retrieval structure 840, which may be arranged adjacently as shown or otherwise, for example, the refrigerated storage may be located at an elevation below the room temperature storage location, where the frozen location is at the lowest elevation level, the refrigerated storage at the next elevation level, the room temperature at the next elevation level, or otherwise. Alternatively, the refrigerated and room temperature storage may be arranged in any suitable and appropriate manner. Additionally, a rear mezzanine 842 may be provided at the room temperature storage and retrieval 838 and the refrigerated storage and retrieval 840 to allow the robot to be removed from the system to room temperature, for example, bagged or insulated from refrigerated to room temperature to prevent condensation on or within the robot. Alternatively, a hot box transfer may be provided. The refrigerated tote storage and retrieval structure 840 may have a refrigerated storage area 846 and a frozen storage area 848, which may be independently refrigerated and insulated, for example to 34°F and 0°F, respectively. Alternatively, the refrigerated storage area 846 and the frozen storage area 848 may be further separated by different temperature levels or temperature gradients sufficient to accommodate a wide range of refrigerated and frozen goods. The refrigerated traffic deck 832 may be separated and insulated from the room temperature traffic deck 830. Similarly, the interior of the refrigerated workstation 828 may be isolated from a picker, who may select individual items from the product totes in a room temperature environment and place them into order totes in the refrigerated interior of the refrigerated workstation. The autonomous robot 822 may move freely between the refrigerated traffic deck and the room temperature deck as described, where the two are separated by insulation and/or a suitable door or divider that isolates the two areas as described below.

The autonomous robotic vehicles or robots 822, 824 may be completely or substantially identical and separated into specific robot types. To allow the robots to place totes closer to the next tote retrieval location during busy periods, the robots may be exposed to long durations in the refrigerated storage or retrieval area. Therefore, the robots may be divided into A-bots 822 and C-bots 824, where A-bots are room temperature bots that are primarily placed in the room temperature storage and retrieval area, and C-bots are refrigerated bots that are primarily placed in the refrigerated storage and retrieval area. An MCS (materials management system) may be provided to manage the watermarks of A-bots and C-bots with dedicated software. As an example, the MCS may be configured such that the waiting A-bots may be stored in a room temperature tower at the rear of the storage and retrieval system, or otherwise. Similarly, the MCS may be configured such that the waiting C-bots may be stored in a room temperature tower at the rear of the storage and retrieval system, or otherwise. In the illustrated embodiment, the storage and retrieval system may accommodate three temperature zones, room temperature, refrigerated, and frozen as described above. Similarly, the totes may be identical or substantially similar, but may be divided into types, for example, to avoid condensation on the product, the totes may be divided into refrigerated totes and room temperature totes.

As described, the robots may be divided into A bots 822 and C bots 824, where A bots are room temperature bots that are primarily located in the room temperature storage and retrieval area, and C bots are refrigerated bots that are primarily located in the refrigerated storage and retrieval area, with "primarily" meaning that the robots spend most, but not all, of the robot vehicle time. As an example, A bots 822 may enter the frozen and refrigerated storage zones to retrieve order totes for distribution. Similarly, C bots 824 may enter the frozen to retrieve and store product totes. As a further option, C bots 824 may deliver O totes near the zone transition point (penetration interlock) to limit the duration that A bots are in the refrigerated or frozen zones. Bot temperatures may be monitored for inter-zone bot transitions (*). Here, the MCS may track and manage the bots based on feedback from internal and external temperature and humidity sensors on the bots. For example, the MCS may calculate the dew point (DP) from the bot feedback for each temperature zone. In one aspect, the bot sensor may indicate that a critical surface is above the dew point. When approaching the dew point, the MCS directs the bot to return to room temperature. Here, the MCS may manage the transition by the following example rules based on configurable attributes, such as minimum inlet temperature for rapid movement (e.g., +10C), abort temperature offset to cancel rapid movement (e.g., +5C), minimum outlet temperature to enter a higher temperature zone (e.g., +2C above DP), allowable (minimum or maximum) residence time in a given zone as a function of the type of bot or any other suitable configurable attribute:

Condensation mitigation may be necessary for a robot. For example, when going from room temperature to refrigerated, no special process may be required. However, when going from refrigerated to room temperature, there may be a need to mitigate condensation, for example, by heating the bot in a hot box 850, where hot box 850 may be a hot plate, an external heater in a "garage bay", or a motion motor in a tower or otherwise. Similarly, condensation mitigation may be necessary for a tote box. For example, when transitioning between tote box types from room temperature to refrigerated, no special process may be required. However, when transitioning between tote box types from refrigerated to room temperature, there may be a need to mitigate condensation, for example, by allowing the tote box to heat up to room temperature or near room temperature by leaving it there for a duration before it can be used.

Continuing with reference to U.S. Patent Application Serial No. 16/831,468, FIGS. 13A, 13B, and 13C show diagrams of a tote box 850. Although the term "tote box" is used herein, tote box 850 may be any of a variety of receptacles, canisters, or other containers for transporting and storing goods, including goods to be transported and stored at different temperatures, as described below. Tote box 850 has a tote box housing 852, a tote box lid 854, and an insulated interior, as described in further detail below. Lid 854 may be hinged by hinge 856 to housing 852, as shown. In alternative aspects, lid 854 may be hinged or hingeless. Lid 854 and housing 852 may be insulated so that heat loss from room temperature may be minimized and so that exterior condensation may be minimized, as described in further detail. The insulation may be conventional, such as a vacuum enclosure or otherwise. By way of example, the insulation may be provided as an insulated insert that insulates a conventional plastic tote box and further accepts a refrigerated or passive liner, as described in further detail. An RFID temperature sensor 858 may be provided on the tote box. In the illustrated embodiment, the RFID sensor 858 is shown at an opposite end of the tote box 850, and a bot having an RFID reader may read the RFID sensor for tote box identification and/or other purposes, such as to read the temperature inside or outside the tote box 850 (in which case the RFID sensor 858 may be a passive temperature sensor enabled by an RFID reader on the bot). Such passive temperature sensors may sense temperature by a thermistor or other temperature sensor connected to a circuit and an RFID antenna. Such sensors are commercially available from RFID suppliers such as Metalcraft of Mason City, IA. In alternative aspects, one or more passive RFID tags and/or sensors may be provided, for example, for temperature, identification, humidity, moisture detection, or other within or outside the tote box assembly. A tab 864 is provided as part of the lid 854 for purposes of opening the lid, either by a human or in an automated manner as described in more detail below. The tab 864 may be formed of the same material as the lid 854, or may be a roller that interacts with a cam or other active or passive mechanism to open the lid 854. Although two tabs 864 are shown, more or fewer may be provided.

FIG. 13B shows a cross-sectional view of tote box 850. FIG. 13C shows a partial cross-sectional view of the upper left corner of tote box 850 as shown in FIG. 13B. Tote box 850 further has insulating wall panels 870, insulating floor panels 872, and insulating lid panels 874. Insulating panels may also be provided at two opposite ends of tote box 850 such that the contents within tote box 850 are completely or substantially surrounded by insulating panels or insulation. Although panels 870, 872 are shown as separate panels, a unitary structure may be provided for insulation, in which case separate panels need not be provided. Although panel 870 is shown with a uniform thickness, in alternative embodiments, the thickness may vary, for example, from top to bottom. Although panels 870, 872 are shown with the same thickness, panels 870, 872 may be of different thicknesses. Similarly, panels 870, 872, and 874 may all be of different thicknesses or the same thickness. A gasket 878 is shown bonded or fastened to a top portion of the insulating panel 870, and the gasket 878 substantially or completely seals the perimeter of the lid 854 to the insulated housing to prevent heat leakage when the lid 854 is closed. The gasket 878 may be a refrigerator type or other suitable type gasket made of EPDM, neoprene, or other suitable material that seals to the lid 854 by compression, magnetic force, or otherwise. If magnetic, a metal insert (not shown) may be provided in the lid 854 that interacts with the seal or gasket 878. In an alternative aspect, the gasket 878 may be bonded or otherwise fastened to the lid 854 to seal the panel 870. The shipping box 850 further includes a thermal insert 882, also referred to herein simply as an insert 882. The insert 882 has a cavity 884 therein. An insert 882 having a cavity 884 is provided in each panel 870 and covers each panel 870 such that the insert 882 and cavity 884 substantially enclose the interior of the shipping box 850. The insert 882 is shown with a floor 886 that protects the panel 872 from damage, for example, by individual items in the shipping box 850. A gap 888 (FIG. 13C) may be provided between the outer surface of the insert 882 and a surface free of the insulating panels 870, 872. This gap may be of any suitable size and is provided to promote circulation of air around the outer and inner surfaces of the insert 882 such that, when the phase change material contained within the insert 882 is regenerated, cooled air touches the surface of the insert 882 surrounding the phase change material, minimizing the amount of time it takes to regenerate the phase change material within the insert 882. The insert 882 may be made from any suitable material, for example aluminum, PVC, or polypropylene. The cavity 884 in the insert 882 may be filled with a suitable material 890, such as a phase change material, to maintain a given set temperature point or range within the tote box 850. The phase change material may be tailored to have a phase transition temperature of -17.2°C (1°F) for a frozen storage temperature window of -17.8 to -15.0°C (0 to 5°F). Similarly, the phase change material may be tailored to have a phase transition temperature of 1.7°C (35°F) for a refrigerated storage temperature window of 1.1 to 4.4°C (34 to 40°F). However, any suitable phase transition temperature and storage temperature window may be provided. In an alternative embodiment, the insert 882 may not include a phase change material, and instead may be made entirely or partially of a suitable material that has sufficient heat capacity to maintain the temperature within the tote box 850. The insert 882, in combination with a suitable material 890, such as a phase change material, has the following characteristics, among others:
1. Because the phase change material is located between the individual items and the insulation, the individual items are directly exposed to the temperature of the phase change material, so the phase transition temperature may be set equal to the set point temperature within the tote box.
2. Provide a uniform medium to maintain a uniform temperature within the tote box 850.
3. It provides a large surface area to facilitate efficient regeneration of the material 890.
4. Provide a removable liner or insert that is easily cleaned and disinfected.
5. Insulation, e.g., vacuum insulation panels 870, protect against damage from the contents within the shipping box 850.

Regarding point 1 above, by placing the phase change material on substantially all of the insulation panels, the individual items are exposed only to the phase change temperature of the insert on all such panels. Any gradient to room temperature is isolated on the exterior of the insert (throughout the insulation panels). This allows for the use of the phase change temperature as a set point. Traditionally, heat entering the tote box through the insulation panels does not hit the "phase change" barrier, and thus the individual item temperatures are exposed to these internal gradients. While material 890 is shown surrounding the interior walls of tote box 850, in alternative aspects material 890 may surround or cover other areas of the interior as well, for example as further described.

Referring to US Patent Application Publication No. 2020/0039746, FIG. 14A shows a plan view of the automated filling workstation 910. FIG. 14B shows a side view of the automated filling station 910. There are two positions 912, 914 where pallets 916 of containers 918 to be filled are positioned for processing. Only one pallet may be processed at a time, allowing an empty pallet to be replaced with a full pallet while a second pallet is being processed. The pallets supply layers of containers 918 to be processed by the workstation, one SKU at a time; multiple layers of containers can be combined for processing, e.g., if they are the same SKU, and loading of all individual items from a given SKU may be completed before any individual items from another SKU are loaded.

A pallet lift 920 may be provided to raise the input pallet so that the top layer of containers is transferred onto a container singulation table 922 for processing. The singulation table feeds the single file containers onto two conveyors 924, 926, which feed the containers into container removal machines 928, 930, respectively, which remove the container packaging material from each container. Once the packaging material is removed, the contained individual items can then be manipulated in groups and bulk-stacked into totes and sub-totes. First, the individual items move onto an accumulation table 932, which accumulates individual items 52 of the same SKU from multiple containers. At the opposite end of the accumulation table, sets of individual items are moved, one at a time, onto a loading staging table 934. There, they are separated into sub-tote groupings by a loading organizer using dividers/manipulators 926 that mirror the configuration of the sub-tote walls. Dividers 936 may include a plurality of dividers that are selectively movable and positionable from the sides of the stacked individual items, some of which may be vertically and horizontally movable on the gantry from above, selectively forming any suitable pattern of dividers to conform to the walls of the tote and/or sub-tote in which the individual items are to be placed or loaded.

The ascending bot travels to the tower 970 and descends to a lower level to deposit the empty tote on the tote handler 940. Directly below the loading staging table is the tote 938 supported by the tote handler 940 and precisely aligned with the load of individual items, i.e., the secondary tote 954 is positioned just below the grouping of individual items. The tote handler 940 may be any suitable vertical indexer whose position and speed can be appropriately controlled. The tote handler 940 may also actively grab the tote in the event that >1g is required or otherwise. Once the load of individual items is properly organized, the surface 942 of the staging table 934 rapidly disappears at very high speeds (much faster than 1g) and completely retracts into the adjacent housing 944. Here, the staging table may be a single table or may be divided as shown. Additionally, the staging table 934 may simply be moved laterally very quickly, moved at a downward angle at high speed, or lowered and then or simultaneously moved laterally to make room. Alternatively, the staging table 934 may be hinged horizontally or vertically to make room for the individual items to be lowered. Alternatively, a multi-piece iris may be used. If the staging table is moved vertically or otherwise, it may be further drilled to prevent suction due to rapid separation from the individual items. The staging table 934 may be moved by actuators including hydraulic, electric, or any suitable actuation.

The box handler 940 brings the box to a stop aligned with the up-bound box conveyor 948 and the down-bound box conveyor 950 (e.g., up-bound and down-bound mobile robots) and a transfer mechanism interfaces those conveyors with the box handler. If the box is to receive another layer of individual items in a second load, it returns to the receiving position directly below the staging table and the process is repeated. Alternatively, the filled box is transferred onto the down-bound conveyor and the empty box is transferred onto the box handler, which returns to the receiving position to be loaded. The organization of the next load of individual items overlaps in time with the unloading of the previous set of individual items, so that the loading cycle can begin as soon as the receiving box 38' is in the loading position.

With reference to US Patent Application Publication No. 2019/0047787, FIG. 15 shows a universal gripper 3110 mounted on a Cartesian robot 3150. The robot 3150 is driven along a pair of rails 3152 by a pair of motors 3154 on the robot 3150. For example, each rail 3152 may include a toothed timing belt drive driven by one through shaft servo motor 3154. The through shaft is mounted on two parallel drives to ensure that the two sides are driven evenly.

The robot 3150 further includes a shaft 3158 that is secured within the hub 3118 of the gripper 3110 to translate and/or rotate the gripper 3110. FIG. 15 is a perspective view of the robot 3150 and gripper 3110 transferring a sub-transport 3102 (sub-transport 3102a) from one transport bin to another. The Cartesian robot and gripper may be mounted within the storage racking to allow for intra-storage transfer of sub-transport bins between entire transport bins. This is used to defragment the storage, i.e., to combine empty sub-transport bins together within an entire transport bin, thereby increasing the storage density within the system.

15 shows the gripper 3110 in a fully raised position. Depending on the tine length, the gripper need not be raised to its full height position when it is not holding a sub-carrier. The drawing also shows the second one-sixth sub-carrier 3102a in a transfer position. The second pair of gripper tines on the opposite side pass through slots in the upper outer flange of this opposite sub-carrier. However, the second pair of tines are driven apart, which allows the second pair of tines to be lifted without lifting the opposite sub-carrier. If it is desired to lift both one-sixth or one-half sub-carriers on both sides of the full carrier, all of the tines are driven apart to position the lifting tabs under the upper outer flanges of both sub-carriers.

The above detailed description has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the description to the precise form disclosed. Many modifications and variations are possible in light of the above teachings. The described embodiments have been selected to best explain the principles and primary applications of the claimed system, thereby enabling others skilled in the art to best utilize the claimed system in various embodiments and with various modifications suited to the particular intended use. For example, rather than simply selecting all of the NFPG products in the G2P system, all or a portion of the products may be selected in the G2P system.
The following items are elements that are claimed in the international application:
(Item 1)
A store for fulfilling orders for merchandise,
a self-service area including shelves of merchandise configured to fulfill self-service orders by shoppers within the store;
a storage area for storing goods and an automated goods-to-person (G2P) area including a mobile robot for fulfilling received orders for goods;
A store in which merchandise having a velocity of sale below a first threshold is replenished to the self-service area by containers in the self-service area and replenished to the G2P area by merchandise from the self-service area to the G2P area.
(Item 2)
2. The store of claim 1, wherein items having a velocity of sale above a second threshold are replenished by containers in both the self-service area and the G2P area.
(Item 3)
2. The store of claim 1, wherein replenishing the G2P area with items from the self-service area allows totes to be filled to a higher density than replenishing the G2P area with items from a container.
(Item 4)
2. The store of claim 1, wherein replenishing the items having a velocity of sale below a first threshold from the self-service area to the G2P area enables the G2P area to operate efficiently using both high velocity items and slow velocity items below the first threshold.
(Item 5)
2. The store according to item 1, wherein the products replenished from the self-service area to the G2P area are transferred in a sub-transport box occupying 1/3 to 1/6 of the transport box.
(Item 6)
2. The store of claim 1, wherein the items having a velocity of sale below the first threshold are unloaded from containers into the self-service area upon pickup at the store.
(Item 7)
13. The store of claim 1, further comprising a computing system having a processor that executes software instructions to implement a replenishment trip algorithm that defines the identities of the items to be replenished, the shelf locations within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items will be placed.
(Item 8)
8. The store of claim 7, further comprising a display for displaying the identity of the items to be replenished, the shelf locations within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items will be placed.
(Item 9)
9. The store of claim 8, further comprising a scanner for scanning identification information of the items, the number of each item picked from a shelf, and the section in which the items are placed when the items are picked from the shelves in the self-service area to replenish the G2P area.
(Item 10)
2. The store of claim 1, wherein the first threshold value is the same as the second threshold value.
(Item 11)
2. The store according to claim 1, wherein the goods are non-frozen packaged goods.
(Item 12)
1. A method for replenishing merchandise in a store, comprising:
(a) replenishing items having a velocity of sale above a first threshold with said containers in an automated goods-to-person (G2P) area of said store;
(b) replenishing said self-service area with said containers within said self-service area with items having a velocity of sale below a second threshold;
(c) replenishing the items having the velocity of sale below the second threshold from the self-service area to the G2P area using individual items.
(Item 13)
13. The method of claim 12, further comprising replenishing items having the velocity of sales above the first threshold with the containers in the self-service area of the store.
(Item 14)
13. The method of claim 12, wherein shelves in the self-service area are depleted by restocking the G2P area and by customer shopping in the self-service area.
(Item 15)
13. The method of claim 12, wherein step (c) enables the items having the velocity of sale below the second threshold to be densely packaged in totes stored in the G2P area.
(Item 16)
13. The method of claim 12, further comprising implementing a replenishment trip algorithm that defines the identities of the items to be replenished, the shelf locations within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items will be placed.
(Item 17)
13. The method of claim 12, wherein the replenishment trip algorithm is performed when the self-service area is closed to customers.
(Item 18)
1. A method of replenishing merchandise in an automated goods-to-person (G2P) area of a store, comprising:
(a) replenishing with said containers within said G2P area of said store items having a velocity of sale above a first threshold;
(b) replenishing items having the velocity of sales below the second threshold from a self-service area of the store to the G2P area using individual items.
(Item 19)
20. The method of claim 18, further comprising generating a list of the items having the velocity of sale below the second threshold for pick-up from the self-service area of the store.
(Item 20)
20. The method of claim 18, further comprising configuring a container with a predefined number of secondary transport bins to receive the individual items used to replenish the G2P area.
(Item 21)
A store for fulfilling orders for merchandise,
a self-service area including shelves of merchandise configured to fulfill self-service orders by shoppers within the store;
an automated goods-to-person (G2P) area including an automated storage and retrieval system comprised of a storage area for storing goods and one or more picking stations for fulfilling received orders for the goods, said storage area having a static storage area and a temporary storage area;
goods having a velocity of sale above a first threshold are replenished to the static storage area of the G2P area by the container;
products for non-same-day orders and having a velocity of sale below the first threshold are replenished from the self-service area to the temporary storage area of the G2P area;
A store in which merchandise for non-same-day orders is picked from both the static storage area and the temporary storage area of the G2P area, and merchandise for same-day orders is picked from the static storage area and the self-service area of the G2P area.
(Item 22)
22. The store of claim 21, wherein items having a velocity of sale below the first threshold are also replenished from the self-service area.
(Item 23)
22. The store of claim 21, wherein merchandise having a velocity of sales below a first threshold is replenished in the static storage area of the G2P area periodically rather than in response to customer orders.
(Item 24)
24. The store of claim 23, wherein items having a velocity of sales below a first threshold are replenished in the static storage area when the store is closed to customers or during off-peak hours.
(Item 25)
22. The store of claim 21, wherein merchandise for non-same-day orders is replenished from the self-service area to the temporary storage area in response to one or more customer orders.
(Item 26)
26. The store of claim 25, wherein items for non-same-day orders are replenished from the self-service area to the temporary storage area when the store is closed to customers or during off-peak hours.
(Item 27)
26. The store of claim 25, wherein the merchandise available in the G2P area for fulfilling non-same-day orders includes all of the SKUs available in the self-service area.
(Item 28)
26. The store of claim 25, wherein merchandise available within the G2P area for fulfilling non-same-day orders is replenished as needed in response to non-same-day orders.
(Item 29)
22. The store of claim 21, wherein inventory is picked from the self-service area for fulfilling same-day orders and for replenishing the G2P area for fulfilling non-same-day orders.
(Item 30)
22. The store of claim 21, wherein inventory for fulfilling non-same-day orders is selected entirely from the G2P area.
(Item 31)
22. The store of claim 21, wherein the amount of storage in the static storage area versus the temporary storage area is determined by an algorithm and changes periodically.
(Item 32)
22. The store of claim 21, wherein if a non-same day order is cancelled, a reverse sort is performed to transfer inventory in the temporary storage area to the self-service area.
(Item 33)
A store for fulfilling orders for merchandise,
a self-service area including shelves of merchandise configured to fulfill self-service orders by shoppers within the store;
an automated storage and retrieval system configured using a storage area for storing containers containing goods and for retrieving containers containing goods;
the automated storage and retrieval system is configured to fulfill non-same-day orders;
products are replenished to the self-service area by the containers;
orders for non-same-day orders of merchandise are picked overnight from the self-service area against order and stored in the containers within the storage area of the automated storage and retrieval system;
A store, wherein the orders for the non-same day orders of merchandise are fulfilled from the automated storage and retrieval system.
(Item 34)
34. The store of claim 33, wherein non-same-day orders are picked from the self-service area to fulfill the order instead of replenishing the storage area.
(Item 35)
34. The store of claim 33, wherein after an order for non-same-day items is stored in the container in the storage area, no further sorting of the order is performed prior to delivery to a customer.
(Item 36)
1. A method of replenishing merchandise in an automated goods-to-person (G2P) area of a store including a self-service area where customers select their merchandise, comprising:
(a) replenishing said self-service area with merchandise using said containers;
(b) selecting items from said self-service area overnight for orders for non-same-day orders;
(c) storing the products selected in step (b) in a container in a storage area of the G2P area;
(d) fulfilling the order for the non-same day order product from the storage area of the G2P.
(Item 37)
37. The method of claim 36, wherein the storage area comprises a static storage area and a temporary storage area, the method further comprising replenishing the static storage area in the G2P area with the containers with items having a velocity of sale above a first threshold.
(Item 38)
38. The method of claim 37, further comprising replenishing the temporary storage area of the G2P area with merchandise for non-same-day orders having a velocity of sale below the first threshold from the self-service area.
(Item 39)
40. The method of claim 38, further comprising the step of selecting merchandise for non-same-day orders from both the static storage area and the temporary storage area of the G2P area.
(Item 40)
40. The method of claim 39, further comprising the step of selecting items for same-day orders from at least one of the static storage area and the self-service area of the G2P area.
(Item 41)
A store that provides products,
a self-service area including shelves configured to buffer merchandise for fulfilling self-service orders selected by shoppers in the store and to buffer merchandise for fulfilling online orders;
an automated goods-to-person (G2P) area including a storage area for storing goods and an automated storage and retrieval system comprised of one or more sorting stations for fulfilling received orders for the goods;
one or more batches of the same SKU product are replenished from the self-service area to the G2P area in response to a plurality of online orders;
A store, wherein within the G2P area, individual online orders are picked from the batch of the one or more same SKU items replenished from the self-service area.
(Item 42)
42. The store of claim 41, wherein the batch of one or more same SKU items replenished from the self-service area to the G2P area is replenished in response to a non-same day online order.
(Item 43)
43. The store of claim 42, wherein the batch of one or more same SKU items replenished from the self-service area to the G2P area is replenished when the self-service area is closed.
(Item 44)
43. The store of claim 42, wherein the batch of one or more same SKU items replenished from the self-service area to the G2P area is replenished during off-peak hours in the self-service area.
(Item 45)
43. The store of claim 42, wherein the batch of one or more same SKU items replenished from the self-service area to the G2P area are persistent items replenished in response to same-day online orders.
(Item 46)
42. The store of claim 41, wherein items are picked directly from the self-service area to fulfill the individual online orders.
(Item 47)
Item 42. The store of item 41, wherein merchandise is picked by shoppers from the self-service area when the self-service area is open, merchandise is picked from the G2P area to fulfill online orders when the self-service area is open, and merchandise is transferred from the self-service area to the G2P area when the self-service area is closed.
(Item 48)
A store that provides products,
a site replenishment area comprising a self-service area, the site replenishment area configured to buffer all merchandise received at the store, including merchandise for fulfilling online orders, the self-service area configured to buffer merchandise for fulfilling self-service orders selected by shoppers in the store;
an automated goods-to-person (G2P) area including a storage area for storing goods and an automated storage and retrieval system comprised of one or more sorting stations for fulfilling received orders for the goods;
one or more batches of the same SKU product are replenished from the site replenishment area to the G2P area in response to a plurality of online orders;
A store, wherein within the G2P area, individual online orders are picked from the batch of the one or more same SKU items replenished from the site replenishment area.
(Item 49)
15. The store of claim 14, wherein the replenishment of the batches of one or more same SKU items from the site replenishment area to the G2P area occurs when the self-service area of the store is closed.
(Item 50)
2. The store of claim 1, wherein the batch of one or more same SKU items replenished from the site replenishment area to the G2P area is replenished in response to a non-same day online order.
(Item 51)
51. The store of claim 50, wherein the batch of one or more same SKU items replenished from the site replenishment area to the G2P area is replenished during off-peak hours in the self-service area.
(Item 52)
51. The store of claim 50, wherein the batch of one or more same SKU items replenished from the self-service area to the G2P area are persistent items replenished in response to same-day online orders.
(Item 53)
50. The store of claim 48, wherein merchandise is picked directly from the site replenishment area to fulfill the individual online orders.
(Item 54)
2. The store of claim 1, wherein merchandise is picked by a shopper from the self-service area when the self-service area is open, merchandise is picked from the G2P area to fulfill an online order when the self-service area is open, and merchandise is transferred from the self-service area to the G2P area when the self-service area is closed.
(Item 55)
1. A method of offering merchandise in a store, comprising:
(a) replenishing merchandise received at the store based on demand for the merchandise at the store;
(b) storing the merchandise replenished in step (a) in a self-service area, the self-service area being provided for buffering merchandise for the fulfillment of self-service orders by shoppers in the store and for buffering merchandise for the fulfillment of online orders;
(c) transferring items from said self-service area to an automated shelf Goods-to-Person (G2P) area for automated fulfillment of online orders;
(d) selecting items from the items transferred from the self-service area to the G2P area in step (c) for fulfilling an online order within the G2P area.
(Item 56)
56. The method of claim 55, wherein the step (c) of transferring merchandise from the self-service area to the (G2P) area includes transferring merchandise for automatic fulfillment of non-same-day online orders.
(Item 57)
56. The method according to claim 55, wherein the step (c) of transferring goods from the self-service area to the (G2P) area comprises the step of transferring a batch of goods for which an order has been received.
(Item 58)
56. The method of claim 55, wherein the step (c) of transferring merchandise from the self-service area to the (G2P) area includes transferring merchandise for automatic fulfillment of non-same-day online orders.
(Item 59)
56. The method of claim 55, wherein the step (c) of transferring merchandise from the self-service area to the (G2P) area includes transferring persistent merchandise for automatic fulfillment of same-day online orders.
(Item 60)
56. The method according to claim 55, wherein the step (c) of transferring goods from the self-service area to the (G2P) area is performed during off-peak hours of the self-service area or when the self-service area is closed.

Claims (32)

A store for fulfilling orders for merchandise,
a self-service area including shelves of merchandise configured to fulfill self-service orders by shoppers within the store;
a storage area for storing goods and an automated goods-to-person (G2P) area including a mobile robot for fulfilling received orders for goods;
A store in which products having a velocity of sale below a first threshold are replenished to the self-service area by containers within the self-service area and replenished to the G2P area by products from the self-service area to the G2P area. The store of claim 1, wherein items having a velocity of sale above a second threshold are replenished by containers in both the self-service area and the G2P area. The store of claim 1 or 2, wherein replenishing the G2P area with items from the self-service area allows tote bins to be filled to a higher density than replenishing the G2P area with items from a container. The store of any one of claims 1 to 3, wherein replenishing the items from the self-service area to the G2P area that have a velocity of sale below a first threshold allows the G2P area to operate efficiently using both high velocity items and items with a low velocity below the first threshold. The store according to any one of claims 1 to 4, wherein the products replenished from the self-service area to the G2P area are transferred in a sub-transport box that occupies 1/3 to 1/6 of the transport box. The store of any one of claims 1 to 5, wherein the products having a velocity of sale below the first threshold are unloaded from containers into the self-service area upon collection at the store. The store of any one of claims 1 to 6, further comprising a computing system having a processor that executes software instructions to implement a replenishment trip algorithm that defines the identity of the items to be replenished, the shelf locations within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items are to be placed. The store of claim 7, further comprising a display for displaying the identity of the items to be restocked, the shelf location within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items are to be placed. The store of claim 8, further comprising a scanner for scanning the identification of the items, the number of each item picked from the shelf, and the section in which the items are placed as the items are picked from the shelves in the self-service area to replenish the G2P area. The store of claim 2, wherein the first threshold is the same as the second threshold. The store according to any one of claims 1 to 10, wherein the goods are non-frozen packaged goods. 1. A method for replenishing merchandise in a store, comprising:
(a) replenishing items having a velocity of sale above a first threshold with containers in an automated goods-to-person (G2P) area of the store;
(b) replenishing the self -service area with containers within the self-service area with items having a velocity of sale below a second threshold;
(c) replenishing the items having the velocity of sale below the second threshold from the self-service area to the G2P area using individual items. The method of claim 12, further comprising replenishing items having the velocity of sale above the first threshold with the containers in the self-service area of the store. The method of claim 12 or 13, wherein shelves in the self-service area are depleted by restocking the G2P area and by customer shopping in the self-service area. The method of any one of claims 12 to 14, wherein step (c) enables the products having the velocity of sale below the second threshold to be densely packaged in totes stored in the G2P area. The method of any one of claims 12 to 15, further comprising implementing a replenishment trip algorithm that defines the identity of the items to be replenished, the shelf locations within the store where the items are located, the desired number of each item to be picked from the shelf, and the size of the section in which the items are to be placed. The method of claim 16, wherein the replenishment trip algorithm is performed when the self-service area is closed to customers. 1. A method of replenishing merchandise in an automated goods-to-person (G2P) area of a store, comprising:
(a) replenishing with containers within the G2P area of the store items having a velocity of sale above a first threshold;
(b) replenishing items having the velocity of sale below a second threshold from a self-service area of the store to the G2P area using individual items. 19. The method of claim 18, further comprising generating a list of the items having the velocity of sale below the second threshold for retrieval from the self-service area of the store. 20. The method of claim 18 or 19, further comprising configuring a container with a predefined number of secondary transport bins to receive the individual items used to replenish the G2P area. A store for fulfilling orders for merchandise,
a self-service area including shelves of merchandise configured to fulfill self-service orders by shoppers within the store;
an automated goods-to-person (G2P) area including an automated storage and retrieval system comprised of a storage area for storing goods and one or more picking stations for fulfilling received orders for the goods, said storage area having a static storage area and a temporary storage area;
Replenishing the static storage area of the G2P area with containers of merchandise having a velocity of sale above a first threshold;
products for non-same-day orders and having a velocity of sale below the first threshold are replenished from the self-service area to the temporary storage area of the G2P area;
A store in which merchandise for non-same-day orders is picked from both the static storage area and the temporary storage area of the G2P area, and merchandise for same-day orders is picked from the static storage area and the self-service area of the G2P area. The store of claim 21, wherein merchandise having a velocity of sale below the first threshold is also replenished from the self-service area. The store of claim 21 or 22, wherein merchandise having a velocity of sale below a first threshold is replenished in the static storage area of the G2P area periodically, rather than in response to a customer order. 24. The store of claim 23, wherein merchandise having a velocity of sale below a first threshold is replenished in the static storage area when the store is closed to customers or during off-peak hours. The store of any one of claims 21 to 24, wherein products for non-same-day orders are replenished from the self-service area to the temporary storage area in response to one or more customer orders. The store of claim 25, wherein merchandise for non-same-day orders is replenished from the self-service area to the temporary storage area when the store is closed to customers or during off-peak hours. The store of claim 25 or 26, wherein the merchandise available in the G2P area for fulfilling non-same-day orders includes all of the SKUs available in the self-service area. The store of any one of claims 25 to 27, wherein merchandise available within the G2P area for fulfilling non-same-day orders is replenished as needed in response to non-same-day orders. The store of any one of claims 21 to 28, wherein inventory is selected from the self-service area for fulfilling same-day orders and for replenishing the G2P area for fulfilling non-same-day orders. The store of any one of claims 21 to 29, wherein inventory for fulfilling non-same-day orders is selected entirely from the G2P area. The store of any one of claims 21 to 30, wherein the amount of storage in the static storage area relative to the temporary storage area is determined by an algorithm and varies periodically. The store of any one of claims 21 to 31, wherein reverse sorting is performed to transfer inventory in the temporary storage area to the self-service area when a non-same-day order is cancelled.

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